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Corporate lawyers are among the most in-demand professionals in our country, thanks to the unique skillset and expertise of such professionals.  When you plan a career in law, curiosity about the general lawyer salary in the country is very normal. The lawyer salary, or specifically, the lawyer salary in India, depends on a lot of parameters and has no single figure as an answer.  In order to find the answer to how much does a lawyer earn in India, one has to look into all of those parameters and get an estimation. The first and foremost parameter would be the category of the lawyer. Whether they are corporate lawyers, patent attorneys, criminal defense lawyers, and so forth. Compared to the other types, the salary of a corporate lawyer is usually on the higher side. However, the best way to determine how much in-demand a job really is through checking how much pay it offers. The average salary of lawyer in India depends on several factors ranging from the high demand in a specific location to the level of experience a lawyer brings to the table. Thus, to help you in understanding the demand of corporate lawyers in India, we have prepared the following article on corporate lawyer salary in India. Let’s get started: What is the Average Corporate Lawyer Salary in India? Take a look at the given figures based on the salary of a lawyer in India to understand how the salary figure works for lawyers based in India. These are estimated ranges of figures which are prone to change lawyer salary in India per month with a change in the company and their offered salary packages. The average corporate lawyer’s salary in India is INR 9.4 Lakh per annum. This figure depends on the base salary, shared profit, and the received bonus.  Source Corporate lawyers are in evergreen demand because of the unique nature of their skill. Organizations of various sectors require the expertise of corporate lawyers to help them get through legal problems. It’s certainly one of the most sought-after professions and as the number of companies in India is increasing, the demand for corporate lawyers is increasing accordingly.  This might have given a rough idea of how much a lawyer earn in India, mainly a corporate one. However, there are many layers in determining a corporate lawyer salary in India. Our Learners also read: Free online Law courses with certificates! Industry is also a factor in terms of how much you earn. Check out how much various industries pay corporate lawyer Industry Salary IT Services & Consulting ₹ 5.5 Lakhs Software Product ₹ 5.8 Lakhs Internet ₹ 7.7 Lakhs Financial Services ₹ 10 Lakhs Legal ₹ 12.4 Lakhs Source Job Description of Corporate Lawyer The job description plays a major role in determining the salary of a corporate lawyer and how much a lawyer earn in India. The more responsibilities they take, the higher their pay gets. Corporate lawyers will guide any company to run under the norms of the legal jurisdiction. They can work in-house, as a consultant, or even as advocates, policymakers, and researchers. From major operational decisions to new mergers to even cases against a company or business deals, corporate lawyers will be needed to set the parameters well. This field has emerged only recently and thus has hordes of opportunities as well as growth options. Corporate law offers immense potential to make it big, given the immense scope involved. If you have the mettle and are also hardworking and thorough in Business Law and sub-areas such as Investment Law, Financial Law, Human Rights, Diligence, Compliance, Environmental Law, IP Laws, Insurance Law, Constitutional Law, and International Trade Law; you can make a plunge in the field of corporate law. This prominently serves as the reason why the salary of a lawyer in India substantially grows with time. Primarily, corporate lawyers advise their clients in business transactions, defend them in lawsuits, claim liability, advise on prosecutions, obligations, and legal rights. They handle all the aspects of corporate law which consists of legal tasks pertaining to the formation, management, and administration of a company (or an entity similar to a company).  Common examples of such enterprises include LLCs (limited liability companies), partnerships, etc. They are responsible for assisting in formatting the new company which requires the filing of various legal documents related to incorporation and ensuring that the company meets all the local, state, and federal regulations. After the formation of a company, the corporate lawyer would advise the business on handling transactions with other corporations for helping the same comply with the regulations.  Corporate lawyers represent their clients in court or before government organizations. They are responsible for presenting and summarizing these cases to judges. In this process, the corporate lawyer might have to collect evidence, evaluate all the findings, and create strategies to present the case. They assist their companies in licensing new technologies and handling any legal issues that may arise. Corporate lawyers have to plan and advise their clients on corporate mergers, large deals, and acquisitions. Due to the unique requirements of their role, corporate lawyers must be experts at the corporate law of their country, state, and locality. They must be familiar with the various rules and regulations related to company formation, compliance, transactions, and other related aspects.  Corporate lawyers have to meet judges, argue motions, analyze laws, question witnesses and interpret regulations with probable case outcomes during a trial. Clearly, they require strong oration and interpersonal skills.  While corporate lawyers work in business hours they might have to work overtime because of the hectic nature of their role and during large transactions, legal cases, or mergers. They work with other legal team members such as patent lawyers to prepare their cases or ensure everything goes smoothly. The upper management of a company relies on the corporate lawyer to assist them with regulatory problems and corporate strategies.  As a corporate lawyer is responsible for meeting with regulators and government agencies, they might have to travel sometimes although the role doesn’t require much traveling. However, a lot of work conditions depend on the kind of enterprise they work with. For example, if your corporation has a lot of satellite offices, you might have to travel frequently.  Getting the top corporate lawyer salary in India depends on a lot of factors. We have discussed the most important determining factors of corporate lawyer salary in India in the next section.  According to a survey by Gallup, despite the scarcity in start-up practice from the lawyers’ end,  60% of lawyers in corporate departments have entrepreneurial ambitions. To become a corporate lawyer, you have to- Complete a bachelor’s degree in law or a related field Complete a relevant internship Apply for a license from the relevant Bar Association Network, work on gaining experience, and work developing a resume.  Factors Affecting Corporate Lawyer Salary in India There isn’t any one-rule-fits-all norm for deciding upon how much does a lawyer earn in India. Your background, credentials, and performance at law school matter at the outset as does your experience and the firm you are seeking employment at to decide the salary of lawyer in India! 1. Location How much do lawyers earn in India greatly varies with their working location. Your location plays a huge role in determining how much you make as a corporate lawyer. Some locations offer salaries higher than the national average while some places offer less than the average pay. It’s important to know which kind of place you live in to calculate your potential earnings in this field. Check out corporate lawyer salary based on location: City Salary Bangalore ₹ 29.3 Lakhs Pune ₹ 9.2 Lakhs Mumbai ₹ 6.6 Lakhs Hyderabad ₹ 8.5 Lakhs New Delhi ₹ 12 Lakhs Kolkata ₹ 5.1 Lakhs Gurgaon ₹ 9 Lakhs Chennai ₹ 7.9 Lakhs Source Top locations for high corporate lawyer salaries in India include Bangalore, Mumbai, and Kolkata. The Corporate Lawyer salary in Bangalore and the Corporate Lawyer salary in Mumbai are among the highest due to the presence of numerous corporate offices. Meanwhile, the Corporate Lawyer salary in Kolkata is also competitive, reflecting the city’s growing business landscape. Additionally, the Corporate Lawyer salary in abroad can be significantly higher, especially in global financial hubs. 2. Skills Another notable factor that affects your corporate lawyer’s salary in India is the skills you have. The unique nature of this role requires you to have a strong grasp on certain skills, especially law-related.  According to the statistics, corporate lawyers with certain skills in their arsenal earn significantly more than others. For example, corporate lawyers with corporate governance skills earn 131% more than the average. Other beneficial skills for these professionals include Mergers and Acquisitions which offers 23% higher pay than the average and Contract Management which offers 70% more than the median pay.  If you want to get lucrative pay then you must focus on developing the most in-demand skills such as Corporate Governance and Contract Management. They will help you get a high-paying job in this field very easily.  3. Experience Wondering how much does a lawyer earn in India? Here is a peek at the average salary of lawyer in India and the factors affecting it. One of the most influential factors in determining your pay is the amount of professional experience you have.  However, after a certain level of experience, your pay in this field increases substantially. Check out how corporate lawyer salary based on experience: Experience Salary 1 Year ₹ 4.2 Lakhs 2 Year ₹ 5 Lakhs 3 Year ₹ 5.5 Lakhs 4 Year ₹ 5.9 Lakhs 5 Year ₹ 6 Lakhs Source 4. Employer When calculating what the average lawyer salary in India per month is, remember that experience with a reputed employer is one crucial parameter that dictates the average salary of lawyer in India and abroad. Finally, a significant influencer of your pay as a corporate lawyer is who you work for. Corporate lawyers can work in various industries as their expertise can be used in nearly all sectors. Companies of all fields have to ensure they follow all the regulations and want to avoid legal issues. Apart from working directly with a company, a corporate lawyer might work in a law firm alongside several other lawyers.  Different employers offer different salaries such as Lexlit Advocates and Solicitors, a law firm, offers up to INR 48,000 to corporate lawyers while EXL Service offers up to INR 62,000.  5. Specialization How much does a corporate lawyer earn in India?  Corporate lawyer salary in India is hugely influenced by their expertise and experience in specific legal domains that are in high market demand.  Topping the charts are private equity, investment banking, capital markets, M&A, taxation, IP, and venture capital law domains where compensation packages can run in crores for niche expertise cultivated over decades of complex high-value deal advisory. As specialization grows more acute to tackle emerging areas like crypto regulations, HR laws, data privacy etc – so does recognition and corporate law salary. With technology disruptions and globalized business landscapes, corporate law itself is evolving.  Domains like AI, ethical hacking, ESG advisory and cross-border M&A require advanced degrees and Ivy League credentials to demonstrate specialized skills. Global exposure becomes vital.  Lawyers cultivating micro-expertise through premium qualifications and multijurisdictional experience in trending areas thus enter the big leagues faster. 6. Negotiation Skills If you want high salary of corporate lawyer in India or tax lawyer salary ensure to sharp business acumen and negotiation brilliance that consistently delivers clear strategic advantage and water-tight risk mitigation for clients also bring in big money for corporate hotshots and no dbout high corporate law salary. Building strong relationships, identifying negotiation levers through astute business sense, having the ability to interpret commercial implications of legal provisions, and crafting airtight contracts that align with clients’ interests – these in-demand skills accelerate both reputation and family lawyer salary. The most successful corporate lawyer salary or criminal lawyer salary are shrewd businessmen first and legal experts next. Intuiting the commercial contexts, strategic priorities and identifying potential negotiating levers comes from years of experience across industries and players.  A keen eye on industry trends, the ability to call out flags, and clarity on implications are key.  Next comes the finesse to steer stakeholders gently towards the optimal middle ground through tactful communication, emotional intelligence, relationship capital, and the flexibility to reassess initial legal positions if needed.  Mastery across domains reveals the business strategist with a holistic vision – the trusted boardroom confidante billion-dollar organizations want by their side. 7. Nature of Clients & Cases Working with marquee Fortune 500 corporations and HNI power promoters on business critical, high-value transactions has a force multiplier effect on lawyers’ fees owing to the complexity and responsibility involved.  High-stakes deals with a larger scope of work allow billing higher hourly rates while enriching experience accelerates career progression and continuity of big-ticket clients. Top lawyers diversify, acquiring a large retainerships and one-off mega deal advisory portfolio. Prestigious clients and high-profile cases become stepping stones to bigger salary for a corporate lawyer and greater complexity in turn. Top-tier lawyer salary or criminal lawyer salary positively reinforce their personal brand by being involved in noteworthy deals and representing respected corporations. 8. Law Firm’s Profitability A law firm’s financial health and profit margins directly impact the salary increments and bonuses extended to its corporate litigation lawyer. Successful elite firms generate high gross revenues through steep billing rates charged to corporate clientele and premium retainer ships for trusted advisory spanning decades.  After accounting for operational overheads and partner profits, the surplus gets invested back into talent retention schemes via meatier salaries and incentives. Rapidly growing firms similarly attract top-notch legal brains via compensation attractiveness.  However, strained balance sheets watch management turn conservative on appraisals and variable pay during slower quarters to restore profitability metrics affecting earnings negatively. Indian Law Firms that Pay the Highest Lawyer Salary in India:  How much do lawyers earn in India also depends on the law firm they are associated with. Top law firms in India can pay up to INR 14 lakh per annum to their employees. Apart from high remuneration these law firms also provide a great opportunity of grooming and prepare their employees to become experts and serve their valuable clients worldwide. These law firms extend the valuable experience to fresher candidates. Below are some of the top law firms for corporate lawyers that heavily influence how much does a lawyer earn in India. 1. Khaitan and Co. Found back in 1911, Khaitan and Co is India’s one of the oldest top law firms. The firm has more than 115 partners. The practice area of the firm includes banking and finance, competition law, dispute resolution, corporate, capital markets, energy, hospitality, infrastructure, intellectual property, funds, labour and employment, infrastructure and resources, and various other fields such as technology, and media, taxation etc. The firm has several national and international clients and has won the prize of being the best law firm of the year. The average salary of a legal associate with an experience of 1 to 5 years in this firm is around INR 10 lakhs per annum. 2. Sahrdul Amarchand Mangaldas & Co This law firm is considered to be the current largest law firm in India with its offices being across several cities of the country, such as New Delhi, Mumbai, Kolkata, Bengaluru, Chennai, Ahmedabad and Gurugram. The firm has a global client base with more than 110 partners all around the world. The firm has also won the “Innovation in Legal expertise” title. An associate with an experience between 1 to 5 years can earn an average of 17 lakhs per annum by working for this firm. The remuneration of associates with experience between 1 to 6 years ranges anywhere between INR 12 lakhs to INR 22 lakhs per annum. 3. Trilegal India Trilegal India is one of the top law firms in India that has employed more than three hundred lawyers across India in the four major cities, Bangalore, Mumbai, New Delhi, and Gurgaon. The firm mainly deals with real estate, infrastructure, energy, technology, and information technology fields. The firm is known for providing a great environment of analytical thinking for budding lawyers. As a fresher of 0 to 1 year, one can get paid an average of INR 14.8 lakh per annum. A legal associate’s salary at Trilegal India ranges from INR 13 lakhs to INR 16 lakhs per annum. 4. Desai & Dewanji Established in 1930, Desai & Dewanji is one of India’s oldest law firms and is widely popular for its high salary structure. The firm primarily deals with clients that are from the field of banking and finance, project and infrastructure, capital market, corporate problems and dispute resolution. The firm is located in three major cities of the country, Mumbai, Delhi and Gurgram. The firm has more than 24 partners and a tidal of more than 185 lawyers across its offices. A legal intern can earn an average of INR 2 lakh per annum by working for the company. Whereas legal associates with an experience between 2 to 6 years can earn anywhere between INR 7.2lakhs to INR 9.7 lakhs per annum. 5. Vaish Associates Founded in 1971, Vaish Associates is a full-service law firm that deals with both national and internal clients. The company has its three major companies in Mumbai, Bangalore and New Delhi, where New Delhi is the headquarters. However, the law firm also provides support in several other metropolitan cities. The firm gained its popularity by dealing in the fields of taxation, corporate, banking and finance, etc. Currently, the company has more than a dozen of partners and hundreds of associates working across the globe. Associate trainees in the company get paid an average of INR 4 lakhs per annum. Whereas associates and Senior Associates with experience between 1 to 7 years earn an average of INR 9.1 to 9.2 lakhs per annum. 6. Talwar Thakore and Associates The corporate law firm founded in 2007 is commonly known as TT&A. Around 60% of their current operations are now international. TT&A collaborated with Linklaters for the first time in 2011. Since then, the two organizations have successfully worked on different international projects together.  The remuneration offered by this corporate law firm begins at Rs 13 lakhs. The firm also provides a hefty bonus spending on factors like devotion to client’s work, performance, and more.  7. S&R Associates S&R Associates is a highly successful law firm established in 2005. Only 20% of its operations are focused on the domestic market. The remaining 80% of work is international. The firm runs on a 50:50 ratio with 6 female and 6 male partners. It is one of the most prestigious firms for a corporate lawyer to work in India.  Apart from corporate law, the firm also covers legal matters related to capital markets, private equity, IT & media, and more.  The firm offers a lucrative corporate lawyer salary of more than Rs 13 lakhs in the beginning. S&R Associates also offer a performance-related bonus to lawyers. The firm hires top talents from educational institutions like ILS, NALSAR, and ILS.  8. J Sagar and Associates JSA is a national law firm with 40 partners and more than 200 lawyers. The corporate law firm has multiple offices in different locations, including New Delhi, Chennai, Mumbai, Hyderabad, and Bangalore. It was established by Jyoti Sagar in 1991.  The firm offers around Rs 11.5 lakhs as the corporate lawyer salary in India. It also offers a lucrative bonus to employees. Moreover, every lawyer working at the firm can expect an increase in their base salary at the end of each year.  How to Get the Top Corporate Lawyer Salary in India? As we discussed in the previous section, your corporate lawyer’s salary in India depends on several factors. However, out of all of those factors, the one you control the most is the skills you have. By increasing the in-demand skills you have, you can enhance the amount you can make. Moreover, we have already seen how certain skills enhance your pay by a huge margin.  There are multiple methods to develop such skills. However, the most efficient method to learn the most in-demand skills is through taking a course. Taking such a course would ensure that you learn all the necessary skills for this role and get the highest chance of earning the top corporate lawyer salary in India. Trending Skills for Corporate Lawyers in India The top skills that you should acquire to earn the average salary of a corporate lawyer in India are as follows: Business Awareness: it is one of the most important skills for a corporate lawyer to understand how businesses work. This skill is essential for understanding the reason behind the success of a business. Sharp business acumen allows lawyer salary or highest paid lawyers to grasp the commercial context behind legal issues faster. They can delve into the strategic motivations, objectives, and challenges underpinning any situation, whether it is drafting an agreement, evaluating risk exposures, or planning compliance regimes. Negotiation Skills: Good negotiation skills are extremely important for getting a high corporate lawyer salary in India. Negotiation skills are essential for settling disputes peacefully outside the court. It saves the cost of expensive litigation. Possessing strong negotiation tactics allows salary for a corporate lawyer or highest paid lawyers to steer stakeholders strategically towards the optimal middle ground during conflicts. By understanding the priorities and constraints of both parties, corporate litigation lawyer identify common goals and creatively structure solutions addressing key concerns without overstretching. Company Law: In-depth knowledge of the Companies Act 2013 is necessary for all corporate lawyers. It helps understand legal aspects associated with appointing company officials, preventing fraud, and more.  With over 470 sections and rules influencing board constitution, corporate governance, audits, shareholder rights, mergers, and wind-ups – mastery over the intricacies of this vast legislation is non-negotiable. Nuances around permissible, conditional, and prohibited activities, compliance requirements, penalties, and exemptions need thorough analysis during advisory. Technology Proficiency: As industries digitize, corporate litigation lawyer equipped with tech skills spanning AI, smart contracts, blockchain, cloud platforms, data science, etc, understand digital business models deeper to customize pragmatic counsel. Evaluating agreements, regulations, and risk exposures around disruptive innovation mandates digital fluency, allowing seamless integration of legal, technology, and business perspectives. With exponential data growth and process automation, most corporate decisions now involve evaluating digital capabilities, privacy needs, security controls, architecture designs, vendor ecosystems, etc., rather than merely traditional products. Without technology context around how platforms operate, their strengths, limitations, and risks – legal oversight gets limited to theoretical scrutiny rather than actionable risk-based guidance. Data Privacy and Cybersecurity Knowledge: As data generation explodes, privacy and security considerations get tightly interwoven across digital initiatives and cloud adoption, requiring cross-functional literacy around global regulations, company security policies, risk management, and incident response across devices, networks, and applications. With data emerging as the most valuable asset today, cyber risks threaten business continuity through data or identity theft, ransomware attacks, and phishing schemes, leading to huge financial and reputation losses. Corporate counsels safeguard organizations by conducting data mapping audits profiling information usage, location, and flows. Overall, data protection mindfulness strengthens the first line of defense. Financial Acumen: Sharpening financial analysis skills helps interpret statements, financial health, and funding scenarios accurately, advising clients on profitability impacts of decisions around fundraising options, M&A, capital allocation, taxation, or compliances, and long-term value creation. Parsing financial statements shrewdly identifies risk exposures early. Analysing past performance guides prudent forecasting. For acquisitions, astute modeling unearths fragile assumptions, indicating overvaluations ahead. Since legal, financial, and growth strategies tightly interlock, proficient corporate advisors speak the CFO’s language – fluently discussing metrics like capitalization tables, NPV, sensitivity analysis, WACC, and valuations multipliers gauging impacts of decisions holistically. Dispute Resolution: With court backlogs averaging around 30 years for commercial suits in India, proficiency in negotiation, mediation and arbitration becomes pivotal for timely dispute resolution saving years, relationships and costs making settlement abilities intrinsic to corporate law capabilities. As backlogs hit crisis proportions, corporate lawyers and patent lawyer salary contribute most value when keeping clients productively out of courts through timely intervention. Deploying alternative resolution mechanisms like mediation, fast-track arbitration or even dynamic negotiation tactics for settling out of court minimizes enterprise paralysis due to disputes. Win-win collaboration mindsets identify solutions addressing root concerns before counterparty relationships turn irreparable. Adaptability and Continuous Learning: Upgrading legal knowledge across jurisdictions on evolving regulations around niche domains like crypto, space laws, and sustainability reporting ensures timely counsel, aiding proofing of innovation and globalization strategies to mitigate compliance blindspots early. With business environment volatility the norm rather than the exception, corporate lawyers continually upgrade their expertise to steer opportunities prudently. Tracking emerging domains and regulatory shifts across key markets proactively future-proofs growth plans for minimized disruption when activating new geographies, products or alliances. Specialists cultivate reliable global peer networks to gain early signals on likely reforms across tax, IP, and M&A norms, helping model impacts on operating plans. Maintaining an ambidextrous outlook and evaluating adjacent possibilities from potential partnerships to M&A targets allows capitalizing on the upside from disruptions swifter. Soft Skills: Honing emotional intelligence, situational judgment, communication, people management, and collaborative abilities smooth client interactions, building mutually trusting relationships, and conflict resolution skills crucial for positive commercial outcomes to get the high corporate lawyer salary in India or patent lawyer salary. People and relationships sit at the core despite corporate law being number-driven by nature. Like emotional radars, soft skills pick subtle cues guiding situational tone alignment to build rapport faster. Conversations turn collaborative rather than transactional by mastering body language, empathetic questioning, and non-verbal listening. Managing expectations comes naturally, preventing future blindsides. During negotiations, slowing down exchanges allows relationships to deepen, perceiving real underlying interests apart from stated positions. Conclusion As you can see, pursuing a career in corporate law is certainly a smart choice. Not only is this role well-respected but it’s also very lucrative and offers tons of growth opportunities. Of course, it is an intensive field that makes you keep engaged in constant study and pressure-laced deadlines too! But the offered average salary of a lawyer in India and the added reputation often lead people to feel an inclination towards this path, which is completely worth it if the candidate is willing to put in the work! Above all, corporate law allows rare latitude to drive enterprise growth journeys, partnering with leadership and navigating ambiguous business environments with strategic counsel. Blending vigilance and ambition to further organizational priorities makes the profession intellectually stimulating and hugely purposeful improving industry dynamics while getting corporate lawyer average salary in India. Do you have any suggestions for this article? Let us know in the comments.

by upGrad

18 Jul 2024

Blogs

90952

In this Article, you will learn about top 14 technical courses to get a job in IT. Software Development Data Science Machine Learning Blockchain Management MBA Cloud Computing Cybersecurity DevOps Web Development Big Data Digital Marketing Business intelligence  Database systems Read more to know each in detail. Top Technical Courses Online To Get a Job in IT Looking for technical courses to get a job in IT? In the last decade, the IT industry has undergone a massive transformation and expansion. Fuelled by fast-evolving new-age technologies, the IT sector is now one of the world’s most promising job destinations! High annual salary packages, in-demand job roles, and plenty of chances to make a standing impact are among the top reasons why a large percentage of the youth are leaning towards IT jobs. For those tech-savvy people, we have listed down the top technical courses to get a job in IT.   The employment sector in IT and Computer Science is projected to grow by 13 percent from 2020 to 2030. Careers in the IT industry are high-paying and fast-growing. The reason for demand in IT companies is due to the evolving nature of technology. Technology is not limited to a few things rather its applications are in each and every field, which requires sound technical expertise and training.  There are many jobs available in the IT field such as Big Data Engineer, Cloud Architect, FSD Developer, Product Manager, etc. The domain is not centric on one country or sector so anybody can make a good career across borders and will find the education qualifications relevant and of importance. You can also check out our free courses offered by upGrad in Management, Data Science, Machine Learning, Digital Marketing, and Technology.  The best thing about choosing an IT career is that IT skills are invaluable to every industry, including IT/ITeS, BFSI, retail, manufacturing, healthcare, education, aerospace, and energy, to name a few.  Keeping pace with the rapidly emerging technologies, numerous job roles in the industry are changing as well. Job profiles like Web Developers, Network Architects, Information Security Analysts, Systems Analysts, Cloud Architects, Computer scientists, Data scientists, etc., are growing at a breakneck speed. Naturally, the different IT domains like Data Science, Artificial Intelligence, Cloud Computing, Cybersecurity, and Project Management will create an increasing demand for skilled and qualified IT professionals. We listed down the top technical courses to get a job in IT.  Check out our Java Bootcamp designed to upskill working professionals. However, since IT roles are transforming, today, aspirants need much more than theoretical knowledge – they need solid technical skills. No wonder the demand for technical courses to get a job in IT is at an all-time high now! In this post, we’re going to discuss the trending technical courses to get IT jobs. Technical courses are designed to provide highly specialized knowledge to aspirants. Usually, technical courses promote a combination of academic training and practical exercises to achieve the all-around development of candidates and develop niche skills.  If you are wondering what technical courses are best for trending IT job roles, make sure to read till the end! 14 Technical Courses for IT jobs 1. Software Development Software Development involves the creation, testing, and maintenance of software applications, frameworks, and tools. It is a core element of IT infrastructure and is also the key to success for businesses of all shapes and sizes. Software development focuses on designing innovative software solutions tailored to meet specific client and business requirements. A software tool/framework can improve employee productivity, streamline business operations, boost ROI, fast track sales, and impart a competitive edge to an organization. Software development courses are one of the preferred option to join to get a job in IT.   Software development is projected to grow to 1039.89 billion dollars by 2027. Source The skills of JavaScript, HTML, Python SQL, etc are in demand. Education in the technical courses for these skills will do a valuable addition to one’s profile which would set them apart from the other job seekers. Also, if someone is already in the industry and wants to accelerate their career in a similar field can also benefit by doing the courses as it would help them to accelerate their career better. Since all businesses, including startups, mid-sized companies, and large corporations, use software tools and solutions, Software Developers/Engineers are prized possessions for any firm. Each year, top companies like TCS, IBM, Deloitte, Accenture, Verizon, Infosys, Amazon, Google, Facebook, etc., hire Software Developers by the bulk. The most in-demand software development skills include full-stack development, backend development, and front-end development.  Today, learning software development has become much easier, thanks to professional software development certifications. Software development certification programs are highly focused on imparting practical skills to candidates, such as UI, UX, web design, backend architecture, etc. How much does a software developer earn in India? Factors affecting software developer salary in India i. Salary by location City Salary Bangalore ₹ 9.7 Lakhs New Delhi ₹ 8.4 Lakhs Mumbai ₹ 8 Lakhs Hyderabad ₹ 8.9 Lakhs Pune ₹ 8.4 Lakhs Chennai ₹ 8.2 Lakhs Gurugram ₹ 9.2 Lakhs Kolkata ₹ 7.9 Lakhs ii. Salary by experience Experience Salary 1 Year ₹ 5.2 Lakhs 2 Year ₹ 6.1 Lakhs 3 Year ₹ 7.1 Lakhs 4 Year ₹ 8.7 Lakhs 5 Year ₹ 10.5 Lakhs iii. Salary by industry Industry Salary IT Services ₹ 8.3 Lakhs Software Product ₹ 10.2 Lakhs Financial Services ₹ 9.2 Lakhs KPO ₹ 11.5 Lakhs Hardware ₹ 8.7 Lakhs Engineering ₹ 8.6 Lakhs Manufacturing ₹ 10.2 Lakhs Source upGrad has a whole suite of technical courses of software development – PG Diploma in Software Development (specialization in Full-Stack Development), PG Diploma in Software Development (specialization in Cybersecurity). Check out Cybersecurity course to upskill yourself and gain an edge. 2. Data Science Data Science is a common terminology in the present industry now, and rightly so. Data Science technologies like Artificial Intelligence, Machine Learning, Deep Learning, and Natural Language Processing have found applications across multiple sectors. This is why Data Science professionals who can work with these technologies are in high demand. Unfortunately, the need for Data Science experts far exceeds their supply. As a result, a large portion of Data Scientists’ job vacancies remains unfilled. Data science courses are one of the preferred courses to get a job in IT.  Source According to the Bureau of Labour Statistics (BLS), the data science industry is expected to grow 14 percent by the year 2028. Also, the research shared in the LinkedIn Emerging Jobs Report has ranked data science among the fastest-growing career. Its job market is expected to grow to 230.80 billion dollars by 2026. (Source) The skills required to be a data scientist are Python, Data Visualisation, Microsoft Excel, Communication, Team work capabilities, etc. In today’s there are modes to learn technical courses for freshers and the experienced. So there is no limit to choices, one can upskill and excel in their careers. The demand-supply gap presents an ideal situation for Data Science aspirants. Several institutions in India offer Data Science certification courses and professional training programs. upGrad is one such institute that offers an array of excellent Technical courses in Data Science, namely Business Analytics Certification Program, PG Certification In Data Science, PG Diploma in Data Science, and Master of Science in Data Science. Professionals can take up these technical courses to uplift their career. The course curriculum includes Big Data, Business Intelligence, Machine Learning, Python Programming, Data Visualisation, Predictive Analytics, Machine Learning, Data Visualization, and Natural Language Processing. upGrad encourages theoretical and practical learning, and hence, candidates work on live projects, case studies, mock interviews, and resume building sessions. They also get one-on-one feedback from instructors and industry-mentors.  Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript How much does a data scientist earn in India? Factors affecting data scientist salary in India i. Salary by location City Salary Bangalore ₹15.5 Lakhs New Delhi ₹13.6 Lakhs Mumbai ₹13.2 Lakhs Hyderabad ₹14.8 Lakhs Pune ₹12.8 Lakhs Chennai ₹13.3 Lakhs Noida ₹13.7 Lakhs Gurgaon ₹14.1 Lakhs ii. Salary by experience Experience Salary 1 Year ₹9.5 Lakhs 2 Year ₹10.5 Lakhs 3 Year ₹11.6 Lakhs 5 Year ₹16.4 Lakhs 8 Year ₹19.9 Lakhs iii. Salary by industry Industry Salary IT Services ₹13.2 Lakhs Internet ₹18.3 Lakhs Software Product ₹16.6 Lakhs Financial Services ₹15.1 Lakhs KPO ₹15.3 Lakhs Source 3. Machine Learning Like Data Science, Machine Learning has a huge fan following among the IT and Data Science communities. The USP of Machine Learning is that it can help create intelligent machines that can learn through experience. Usually, ML systems are fed with colossal amounts of data and trained to perform specific tasks for unique scenarios. ML courses are one of the preferred technical courses to get a job in IT.  The global machine learning market is expected to grow to US 121 billion dollars by 2030 (Source). There are certain skillsets which are a prerequisite for this domain such as coding, mathematics, data visualisation, programming, communication, team work, etc. There are also certain important job roles available in this domain such as, machine learning engineer,  data scientist, software developer, AI developer, AI architect, data analyst, etc. These are high paying job roles so the technical courses for it job can open many opportunities for a good career. Companies around the world are using Machine Learning to develop innovative solutions to cater to dynamic customer needs. Some of the most promising Machine Learning roles are ML Scientist, ML Engineer, ML Analyst, Business Intelligence Developer, and NLP Scientist. The cherry on top – these IT job roles come with hefty salary packages! Aspirants who want to enter the Machine Learning domain should opt for ML certification programs. upGrad has six outstanding technical courses in ML, including  PG Certification in Machine Learning & NLP, PG Certification in Machine Learning & Deep Learning, PG Diploma in Machine Learning and AI, Master of Science in Machine Learning and AI. These technical courses focus on supervised learning and unsupervised learning and other relevant topics like Computer Vision, Sentiment Analysis, Neural Networks, Natural Language Processing, Regression Analysis, Object Detection, Gesture Recognition, Information Extraction, and Statistical Pattern Recognition.  You can also check IIT Delhi’sMachine Learning Programin association with upGrad. IIT Delhi is one of the most prestigious institutions in India. With more the 500+ In-house faculty members which are the best in the subject matters. Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses How much does a machine learning engineer earn in India? Factors affecting machine learning engineer salary in India i. Salary by location City Salary Bangalore ₹10.5 Lakhs New Delhi ₹9.2 Lakhs Mumbai ₹8.6 Lakh Hyderabad ₹10.1 Lakh Pune ₹8.4 Lakh Chennai ₹8.8 Lakh Noida ₹9.0 Lakhs Gurgaon ₹10.6 Lakh ii. Salary by experience Experience Salary 1 Year ₹7.0 Lakh 2 Year ₹7.8 Lakh 3 Year ₹9.4 Lakhs 4 Year ₹12.2 Lakhs 5 Year ₹15.1 Lakhs iii. Salary by industry Industry Salary IT Services & Consulting ₹9.5 Lakhs Internet ₹13.8 Lakhs Software Product ₹12.2 Lakhs Financial Services ₹9.1 Lakhs Analytics & KPO ₹14.6 Lakhs Source 4. Blockchain We know Blockchain as the technology that revolutionized the banking and financial services sector. Bitcoin, the cryptocurrency, was the primary reason why Blockchain rose to fame. Essentially, a Blockchain refers to a digital ledger (a record) of transactions that is duplicated and distributed across multiple computer systems within a network. The blockchain market is expected to grow at CAGR of 33.4%. It’s valuation in the market is also expected to reach to  US 55.2 Bn by 2032. (Source). There are certain blockchain skills which are a prerequisite for this industry such as cybersecurity and cryptography, computer programming, data structure, etc. In each block of a Blockchain, there are several transaction records. Every time a new transaction is added to the Blockchain, the new record of that transaction is added to each participant’s ledger. Distributed Ledger Technology (DLT) is the secret behind the management of Blockchain. Blockchain courses are one of the preferred courses to get a job in IT.  There are many job roles available in the blockchain market such as, software engineering, marketing, operations, finance, operations, etc. Source Since Blockchain records information in a way that makes it nearly impossible to hack or violate the system, it is being adopted by numerous industrial sectors like cybersecurity, healthcare, supply chain management, logistics, and transportation, to name a few. Soon, Blockchain technology will find applications in other industries as well. This, in turn, will increase the demand for certified Blockchain experts like Blockchain Developer, Blockchain Engineer, Blockchain Solution Architect, Blockchain Project Manager, Blockchain UX Designer, and Blockchain Consultant.  Anyone who desires to bag such promising job roles in Blockchain should check out upGrad’s technical courses on Blockchain like PG Certification in Blockchain, PG Diploma in Software Development and Blockchain Specialization, and Executive Program in Blockchain Technology Management. These are thoroughly technical courses encompassing relevant subjects like Smart Contracts, Consensus Algorithms, Cryptography, Proof of Concepts, P2P Networks, Distributed Apps, and Blockchain platforms, namely Ethereuem, Hyperledger, Fabric, and Composer.  In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses How much does a blockchain developer earn in India? Factors affecting blockchain developer salary in India i. Salary by location City Salary Bangalore ₹ 9.1 Lakhs New Delhi ₹ 7.1 Lakhs Mumbai ₹ 7.1 Lakhs Hyderabad ₹ 7.1 Lakhs Pune ₹ 6.3 Lakhs Chennai ₹ 6.6 Lakhs Noida ₹ 11.8 Lakhs Ahmedabad ₹ 5.6 Lakhs ii. Salary by experience Experience Salary Fresher ₹ 7.1 Lakhs 1 Year ₹ 7.6 Lakhs 2 Year ₹ 7.4 Lakhs 3 Year ₹ 9.9 Lakhs 5 Year ₹ 12.9 Lakhs iii. Salary by industry Industry Salary IT Services ₹ 8.6 Lakhs Internet ₹ 16.2 Lakhs Software Product ₹ 13.8 Lakhs Financial Services ₹ 7.9 Lakhs KPO ₹ 9.6 Lakhs Source 5. Management Although not a technical course per se, project management is a pivotal component of a company’s IT infrastructure. IT is not confined to developing, testing, and deploying software products and services, but it is also about offering timely deliveries, managing the products/services, and offering customer support. This is where project management enters the scene. A Project Manager’s role in an IT firm is to plan the project outlines, determine the budget, oversee te production operations, and ensure that clients get all the deliverables in time. In other words, Project Managers take on supervisory and managerial roles in an organization.  Aspirants who wish to bag managerial posts and other senior-level roles in IT companies must have management certifications and industry experience. upGrad’s PG Program in Management and Product Management Certification Program are two excellent short-term courses covering industry-relevant topics like Product Development & Planning, User Design, Business Analytics, Business Growth Strategies, and Engagement & Growth. Since these are management courses, they encourage the overall grooming of candidates. So, students are also trained to develop soft skills like strategic thinking, problem-solving, time-management, and interpersonal and communication skills.  Also Read: Short Term Job Oriented Courses 6. MBA Another non-technical but essential IT skill is business administration, and what better than an MBA degree to gain this skill?  A Master of Business Administration program is designed to impart academic, practical, and comprehensive knowledge of an organization’s business administration and business management. MBA courses come in many different specializations, including marketing, finance, accounting, human resources, business communication, business law, business ethics, managerial economics, operations management, etc. The USP of MBA courses is that students are trained to apply classroom knowledge into real-world projects and case studies. This helps them to develop business and management skills that can be applied to a host of industries. One can pursue MBA programs either full-time or via correspondence.  Globally, there’s a massive demand for MBA graduates because they possess in-depth knowledge of business administration matters and possess high-level management skills. An MBA degree can get you well-paying job roles such as Marketing Manager, Human Resources Manager, Finance Manager, Operations Manager, Project Manager, International Business Manager, Digital Marketing Manager, Data Analytics Manager, and IT & Systems Manager.  upGrad has nine online MBA courses – MBA (Global) Deakin Business School, MBA Liverpool Business School, MBA From Golden Gate University, MBA in Digital Finance & Banking (O.P.Jindal Global University), MBA (Global) Deakin Business School, MBA from Liverpool Business School (Specialization in Marketing), MBA from Liverpool Business School (Specialization in Finance), MBA from Liverpool Business School (Specialization in Operations), and MBA from Liverpool Business School (Specialization in Strategy & Leadership).  Also, visit upGrad’s Degree Counselling page for all undergraduate and postgraduate programs. Read our Popular Articles related to Software Development Why Learn to Code? How Learn to Code? How to Install Specific Version of NPM Package? Types of Inheritance in C++ What Should You Know? 7. Cloud Computing  The global cloud computing market forecast indicates that the industry is predicted to rocket from USD 250.04 billion in 2021 to USD 791.48 billion in 2028, with a CAGR of 17.9%. Industries are pivoting to cloud solutions for scalability, flexibility, and cost-effectiveness.  The best course for IT jobs covers cloud infrastructure, services, and business applications. We learn how to interact with popular platforms like AWS, Azure, and Google Cloud and concepts like virtualization, microservices, and cloud-native programming.   Some of the vital roles and responsibilities we have to perform in cloud computing after finishing the best course for IT jobs:  Develop, build, and maintain cloud infrastructure solutions.   Optimize cloud architecture for performance, dependability, and cost-effectiveness.   Work with cross-functional teams to integrate cloud services.   Monitor cloud performance, fix problems, and adopt security measures.  Some of the top career options and their expected salaries are:   Top Career Options  Average Salary (2024)  Cloud Software Engineer  $110,000  Cloud Architect  $132,816  Cloud Software Developer  $78,045  How much does a cloud computing engineer earn in India? Factors affecting cloud computing engineer salary in India i. Salary by location City Salary Bangalore ₹ 7.5 Lakhs New Delhi ₹ 7.6 Lakhs Mumbai ₹ 6.3 Lakhs Hyderabad ₹ 7.4 Lakhs Pune ₹ 7.3 Lakhs Chennai ₹ 6.9 Lakhs Noida ₹ 7.6 Lakhs Kolkata ₹ 7.6 Lakhs ii. Salary by experience Experience Salary 1 Year ₹ 5.2 Lakhs 2 Year ₹ 6 Lakhs 3 Year ₹ 6.2 Lakhs 5 Year ₹ 9.1 Lakhs 7 Year ₹ 12.3 Lakhs iii. Salary by industry Industry Salary IT Services ₹ 6.9 Lakhs Internet ₹ 8.9 Lakhs Software Product ₹ 8.3 Lakhs Financial Services ₹ 8.1 Lakhs KPO ₹ 5.6 Lakhs  8. Cybersecurity  Wondering which course is best for IT jobs? With the global cybersecurity market projected to reach $376.32 billion by 2029, there’s a pressing demand for competent professionals to combat rising cyber threats.  The best course for IT jobs provides complete training in threat detection, encryption methods, and risk management procedures. Practical courses on security protocols, techniques, and technologies help students gain industry certifications such as CISSP, CISM, and CEH.   In cybersecurity, some of the vital roles and responsibilities we have to undertake are:  Implement security measures to protect computer systems and networks.  Monitor networks for security breaches and investigate violations.  Develop and implement security policies and procedures.  Conduct security audits and risk assessments.  Some of the top Career options and their salaries after finishing the top IT courses in demand are:   Top Career Options  Average Salary (2024)  Cybersecurity Forensic Analyst  $79,000  Security Consultant  $95,367  Ethical Hacker  $85,720  How much does a cybersecurity expert earn in India? Factors affecting cybersecurity expert salary in India i. Salary by location City Salary Bangalore 11.7 New Delhi 10.1 Mumbai 12.4 Hyderabad 11.4 Pune 12.9 Chennai 10.5 Noida 10.5 Kolkata 12.8 ii. Salary by experience Industry Salary IT Services ₹ 11.8 Lakhs Software Product ₹ 9.2 Lakhs Financial Services ₹ 9.2 Lakhs KPO ₹ 9.5 Lakhs Food processing ₹ 10 Lakhs Law enforcement ₹ 10 Lakhs Manufacturing ₹ 15.2 Lakhs iii. Salary by industry Experience Salary 3 Year ₹ 8.6 Lakhs 5 Year ₹ 11.5 Lakhs 6 Year ₹ 12.9 Lakhs 8 Year ₹ 16.4 Lakhs 10 Years ₹ 17.5 Lakhs Source  9. DevOps  Wondering which IT course is best for high salary? By the end of 2022, the DevOps market is expected to hit an impressive mark of $8.88 bn and reach $10.84 bn in 2023. It represents continuous and sustained growth. During 2022, it stands at $9.6 billion, but it is to extend to $57.9 billion and is targeted to have a compound annual growth rate (CAGR) of 24.2% up to 2030.  The top IT courses in demand cover agile methodology, CI/CD workflows, and tools like Docker, Kubernetes, and Jenkins. Students learn to handle infrastructure as code, automate the software delivery process, and integrate the development and operations.   As DevOps professionals, our responsibilities encompass:  Automate the software creation, testing, and deployment processes.  Manage Infrastructure and configure using code.  Monitor system performance and fix problems.  Implement and manage CI/CD pipelines to ensure continuous delivery.  Some of the top career options and their salaries are:   Top Career Options  Average Salary (2024)  DevOps Engineer  $105,140  DevOps Architect  $127,172  Automation Engineer  $83,683  How much does a DevOps Engineer earn in India? Factors affecting DevOps Engineer salary in India i. Salary by location City Salary Bangalore ₹ 8.5 Lakhs Pune ₹ 8.6 Lakhs Mumbai ₹ 8.4 Lakhs Hyderabad ₹ 8.3 Lakhs New Delhi ₹ 8.5 Lakhs Kolkata ₹ 7.6 Lakhs Gurgaon ₹ 8.8 Lakhs Chennai ₹ 8.4 Lakhs ii. Salary by experience Experience Salary 2 Year ₹ 5.7 Lakhs 3 Year ₹ 6.6 Lakhs 5 Year ₹ 9.8 Lakhs 6 Year ₹ 11.4 Lakhs iii. Salary by industry Industry Salary IT Services & Consulting ₹ 8.4 Lakhs Software Product ₹ 9.3 Lakhs Internet ₹ 10.2 Lakhs Financial Services ₹ 9.1 Lakhs BPO & KPO ₹ 8.3 Lakhs Source  10. Web Development  The web development industry is forecasted to grow by about 16 percent from 2022 to 2032, driven by rising demand for websites and web applications across industry domains. The more businesses compete in the digital space, the more the demand for web developers who can design dynamic and easy-to-use websites.  In this best IT courses for high salary, the basics of HTML, CSS, JavaScript, and web development tools are covered. Students learn to build dynamic websites, use back-end application programming interfaces, and utilize frameworks like Angular and React. The essential skills include expertise in front-end and back-end development areas, frameworks, and version control systems knowledge.  In the best IT courses for high-salary web development, our roles and responsibilities revolve around the following:  Create, implement, and manage online apps and websites.  Put in place interactive and responsive user interfaces.  To integrate front-end code, work together with back-end engineers and designers.  For optimum performance and compatibility, test and debug the code.  The best career options and their salaries are:   Top Career Options  Average Salary (2024)  Front-end Developer  $83,033  Back-end Developer  $96,000  Full Stack Developer  $84,806  Factors affecting software developer salary in India i. Salary by location City Salary Bangalore ₹ 10 Lakhs Pune ₹ 9.7 Lakhs Mumbai ₹ 8.1 Lakhs Hyderabad ₹ 9.7 Lakhs New Delhi ₹ 8.3 Lakhs Kolkata ₹ 9.2 Lakhs Gurgaon ₹ 10 Lakhs Chennai ₹ 9 Lakhs ii. Salary by experience Experience Salary 1 Year ₹ 4.7 Lakhs 2 Year ₹ 6.2 Lakhs 3 Year ₹ 7.9 Lakhs 4 Year ₹ 9.7 Lakhs 5 Year ₹ 11.5 Lakhs iii. Salary by industry Industry Salary IT Services & Consulting ₹ 9 Lakhs Software Product ₹ 9.7 Lakhs Internet ₹ 11.1 Lakhs Financial Services ₹ 10.8 Lakhs BPO & KPO ₹ 7.5 Lakhs  11. Big Data  Today, companies are using big data analytics to discover insights for their data-driven decisions, and the demand for competent big data professionals is increasing by leaps and bounds. The analytics data market is forecasted to grow to $103 billion by 2027, which will need analysts with data processing, analytics, and visualization skills.  Large-scale processing, storage, and analysis tools and methodologies like Hadoop, Spark, and NoSQL databases will be covered in the best IT certifications for jobs course. Students learn to utilize data visualization and machine learning procedures to extract insight from big and complex data sets. Data processing skills, machine learning, and big data technology acumen are vital.  As professionals in the field of big data, the responsibilities include:  Gather, handle, and evaluate vast amounts of data.  Create and manage ETL procedures and data pipelines.  Distributed computing frameworks such as Hadoop and Spark should be implemented and optimized.  Create and manage data warehouses and databases.  Produce reports and insights through data analysis.  Some of the top career options and their salaries are:   Top Career Options  Average Salary (2024)  Big Data Engineer  $96,412  Data Scientist  $100,099  Data Analyst  $66,828  How much does a big data developer earn in India? Factors affecting big data developer salary in India i. Salary by location City Salary Bangalore ₹ 10.5 Lakhs New Delhi ₹ 9 Lakhs Mumbai ₹ 8.9 Lakhs Hyderabad ₹ 10 Lakhs Pune ₹ 9.6 Lakhs Chennai ₹ 9.1 Lakhs Noida ₹ 9.4 Lakhs Kolkata ₹ 8.3 Lakhs ii. Salary by experience Experience Salary 1 Year ₹ 6.5 Lakhs 3 Year ₹ 8.5 Lakhs 5 Year ₹ 12.5 Lakhs 6 Year ₹ 14.9 Lakhs 8 Year ₹ 15.9 Lakhs iii. Salary by industry Industry Salary IT Services ₹ 9.4 Lakhs Software Product ₹ 11.6 Lakhs Financial Services ₹ 10.6 Lakhs KPO ₹ 11.9 Lakhs Hardware ₹ 13.6 Lakhs Telecom ₹ 13 Lakhs Manufacturing ₹ 13.6 Lakhs Source  12. Digital Marketing  The Worldwide digital advertising budget is expected to increase from $333.25 billion in 2019 to $517.51 billion in 2023. The demand for digital marketing expertise is increasing, and more businesses have started using online platforms.  The best IT courses in demand cover digital marketing techniques and technologies like PPC advertising, email marketing, social media marketing, and SEO.   In the best IT courses without coding digital marketing, we are responsible for the following:  Develop and implement digital marketing strategies to drive online traffic and engagement.  Manage social media accounts and online advertising campaigns.  Analyze website and campaign performance using web analytics tools.  Create content for various digital channels, including social media, email, and blogs.  Some of the top career options and their expected salaries are:  Top Career Options  Average Salary (2024)  Digital Marketing Specialist  $54,000  SEO Analyst  $55,883  Social Media Manager  $57,126  How much does a digital marketer earn in India? Factors affecting digital marketer salary in India i. Salary by location City Salary Bangalore ₹5.5 Lakh New Delhi ₹4.2 Lakh Mumbai ₹3.7 Lakh Hyderabad ₹4.8 Lakh Pune ₹4.6 Lakh Chennai ₹4.1 Lakh Noida ₹3.7 Lakh Ahmedabad ₹3.9 Lakh ii. Salary by experience Experience Salary Fresher ₹2.8 Lakhs 1 Year ₹2.7 Lakhs 2 Year ₹3.4 Lakhs 3 Year ₹4.2 Lakhs 4 Year ₹5 Lakhs 5 Year ₹5.7 Lakhs 6 Year ₹6.5 Lakhs iii. Salary by industry Industry Salary IT Services ₹6.8 Lakh Internet ₹6.7 Lakh Software Product ₹5.1 Lakh Financial Services ₹6.7 Lakh KPO ₹5.1 Lakh Source 13. Business Intelligence  Searching which course is best to get a job in IT sector? As companies attenuating their efforts to data for strategic decision-making is high, there is a high demand for business intelligence professionals. By 2022, the global business intelligence market will grow to USD 39.25 billion and expand to USD 65.94 billion by 2030.  During this top IT certifications in demand today course, students will learn various data analytics tools and techniques for data warehousing, data mining, and visualization.   The roles and responsibilities of business Intelligence professionals involve  Create data models and dashboards for reporting and analytics.  Extract, transform, and load data from various sources.  Analyze data for trends, patterns, and insights.  Interpret data and provide practical suggestions to stakeholders.  Collaborate with business users to determine reporting needs.  Some of the top career options and their expected salaries are:   Top Career Options    Average Salary (2024)    Business Intelligence Analyst    $75,000    Data Analyst    $66,828    Business Analyst    $74,405    How much does a business intelligence analyst earn in India? Factors affecting business intelligence analyst salary in India i. Salary by location City Salary Bangalore ₹ 8.9 Lakhs New Delhi ₹ 8.2 Lakhs Mumbai ₹ 7.4 Lakhs Hyderabad ₹ 8.3 Lakhs Pune ₹ 7.8 Lakhs Chennai ₹ 7.4 Lakhs Noida ₹ 7.5 Lakhs Gurgaon ₹ 7.3 Lakhs ii. Salary by experience Experience Salary 1 Year ₹ 6.0 Lakhs 2 Year ₹ 7.0 Lakhs 3 Year ₹ 8.0 Lakhs 4 Year ₹ 9.1 Lakhs 5 Year ₹ 10.0 Lakhs iii. Salary by industry Industry Salary IT Services & Consulting ₹ 8.1 Lakhs Internet ₹ 10.8 Lakhs Software Product ₹ 10.8 Lakhs Financial Services ₹ 7.5 Lakhs Analytics & KPO ₹ 8.7 Lakhs Source  14. Database Systems  The size of the international Database Management Systems (DBMS) market exceeding $125 billion is expected to grow by 2026.  In this best course for IT jobs, students learn about RDBMS, SQL query language, database modeling, and transaction management. Students learn to develop and optimize databases for effectiveness, safety, and scalability.   DBMS job responsibilities encompass:  Design, implement, and maintain databases to store and retrieve data efficiently.  Optimize database performance through indexing and query optimization.  Ensure data integrity, security, and availability.  Develop and maintain database schemas and data models.  The top Career Options and their salaries are:   Top Career Options  Average Salary (2024)  Database Administrator  $78,000  Database Developer  $82,766  Data Architect  $132,567  Why Seek a Career in IT? The following are some of the most prominent advantages of pursuing the best course for IT jobs: Education and training requirements- Initially, the prerequisites for education and training display significant variability, and in certain instances, one can manage with minimal formal education. Unlike professions in the medical domain, which typically necessitate a period of ten years or more of education and training, initiating the best course for IT jobs demands just a couple of years to amass the requisite knowledge and experience. Certifications and credentials offer efficient and cost-effective avenues for delving into various IT specializations, substantiating your field experience, and advancing your career. While it’s evident that specific sub-fields within IT impose greater demands than others, continuous learning, and training usually prove advantageous in a swiftly evolving sector. Nonetheless, you should not encounter numerous stringent barriers obstructing your entry point. Unlimited options- Within the best course for IT jobs, numerous employment opportunities warrant exploration, each presenting distinct advantages, drawbacks, and experiential dimensions. For instance, you might embark on a path as a computer programmer, engaging in developing novel software or tailored solutions. Alternatively, you could carve a niche as a quality assurance (QA) tester dedicated to optimizing the quality of existing products. For those inclined towards more intricate technical challenges, network engineer or systems analyst roles offer intriguing possibilities. The range of prospects is virtually boundless, permitting you to pursue various avenues. Earning potential- Yet another notable benefit within the domain of IT pertains to the potential for lucrative earnings. Even at the introductory level, IT roles play a pivotal role in an organization’s expansion, and a significant scarcity of IT expertise exists. This scarcity has the effect of elevating wage and salary levels. Initially, you will command a respectable income, and as you accumulate further expertise, your earnings will correspondingly increase. Hiring demand- Every single global organization necessitates the presence of IT personnel, whether it pertains to designing novel products, enhancing security measures, or simply facilitating the administration of devices and applications within the entity. Consequently, the call for IT experts remains substantial and consistently on the rise. Resources such as ISACA’s yearly State of Cybersecurity survey report furnish valuable observations into these recruitment patterns, employee retention, and sought-after proficiencies, enabling you to remain abreast of industry developments. If you possess the appropriate skill set and exhibit a commitment to continuous growth and advancement, the likelihood of facing unemployment becomes exceedingly remote. Remote work potential- While the concept of remote work might not resonate with everyone, it holds immense appeal for a significant portion of individuals. The concept of remote work has gained extensive recognition across various sectors, particularly during the COVID-19 pandemic. Embracing remote work not only provides heightened flexibility and alleviates the necessity of enduring a daily commute but also wields the potential to enhance productivity. Although the best course for IT jobs does mandate physical presence, numerous positions can be effectively executed remotely, contingent upon the availability of a capable computer and a dependable internet connection. Career flexibility- Imagine commencing an IT career only to find that your enthusiasm wanes—perhaps due to the emergence of monotony or a perceived lack of the desired growth potential. The silver lining is that a substantial portion of your skill set remains adaptable. As previously discussed, several best course for IT jobs provides ample room for transition. Should uncertainty continue to shroud your long-term aspirations, the IT field assures a comforting prospect of future flexibility, assuring you that change is feasible. Learn more: Top 9 Hottest Tech Skills Companies are Looking For Conclusion In the fiercely competitive IT job market, I’ve found that pursuing top technical courses is crucial for career advancement. These six courses, in particular, have been instrumental in broadening my domain knowledge and propelling me toward senior-level positions. Sharing from my experience, I believe that equipping oneself with specialized technical skills is essential for anyone aspiring to excel in the IT field. Happy learning!

by upGrad

15 Jul 2024

Blogs

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A Full stack developer is an engineer who can design and develop an end-to-end application independently by handling all the work of coding, databases, servers and platforms. Full stack projects can be further classified as web stack, mobile stack or native application stack depending on the solution stack being used.  As more and more companies are looking to hire full stack developers in India, “Full-stack developer” is a title that every other coding/development engineer wants to update in their LinkedIn and Facebook. Being a full stack developer, you will need to know all of the technologies that are required to build an application from scratch. To become full stack developers, most engineers want to expand their skills horizontally. But unless the skills are known in-depth, the claim will remain a hollow title. If you are upgrading your skills to become a full stack developer, be sure to learn all the technologies in its full depth of understanding. Doing hands-on projects can help you gain in-depth knowledge. Also, Check out our free courses In this article, we will discuss 9 full stack coding project ideas with source code you can try out. You should choose different languages, databases and frameworks for different projects. You may choose technology combinations from the examples below Front-end languages: HTML, CSS, Javascript etc Front-end frameworks: AngularJS, React.js, Bootstrap, jQuery, SASS, Foundation, Semantic-UI, Materialize, Express.js, Backbone.js, Ember.js etc. Back-end: PHP, C++, Java, Python, JavaScript, Node.js Back-end frameworks: Django, Express, Laravel, Rails, Spring etc Database: Oracle, MongoDB, MySQL Check out upGrad’s Java Bootcamp Learn to build applications like Swiggy, Quora, IMDB and more 9 Full Stack Coding Project Ideas & Topics 1) Content Management System for a blog WordPress and Drupal would be the best examples of full stack web app development project ideas for students. Using the CMS users must be able to design a web page using the drag and drop method. Users should be able to add textual or media content into placeholders that are attached to locations on the web page using drag and drop method. This way, users should be able to design the whole website. Users must also get an option to publish blog posts. For this, you need to have a text editor component that accepts user input text and converts it into HTML and push into a database. The website must be published over HTTP and HTTPS protocols such that the blog posts are served from the database and displayed to the visitors in the page template designed by the blog owner.  Source Code: Content Management System for a blog Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses 2) Multi-client website offering client services Here merchants are your primary customers. Merchants must be able to sign up at the site and create a page for themselves that display a list of their services and the pricing. The users who are customers to your customers should be able to sign up as users and purchase goods or services from the merchants. There should be a standard checkout process throughout which is integrated into a payment gateway system.  Enroll in Software Engineering Courses from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. The site could offer different categories of services, like home, beauty, pet, etc. Merchants can select their category when signing up. Customers can browse and search for merchants by category. Merchants can customize their pages with images, descriptions, availability, and other service details. The checkout process should securely collect customer and payment information. Integrating a payment gateway allows for secure credit card processing. Email receipts can be sent to the customer and merchant after purchase. Merchants should have a dashboard to view orders and manage their accounts. Customers can leave reviews and ratings for merchants. Additional features could include appointment scheduling, notifications, customer accounts and order history. The multi-tenant structure allows easy scaling as more merchants and customers join the platform. Robust admin tools help manage users, categories, disputes, and platform growth over time. The core functionality connects service providers to customers in a seamless online marketplace. Source Code: Multi-client website offering client services 3) e-commerce website for automotive parts Under this project, you can develop a standard e-commerce website that displays products to be sold. Users should be able to select the products they want to buy and add them to cart. Users must then be able to make payments via a secure payment gateway. The site would focus on selling automotive parts and accessories, like brake pads, batteries, tires, engine parts, lights, electronics, tools, and more. Customers can browse parts by make/model or general categories. Product information includes specifications, images, reviews, related/alternate parts, and availability. An intelligent search helps customers find the right parts. The shopping cart saves selected items persistently across sessions until checkout. Customers provide shipping and billing information and payment via integration with a payment processor like Stripe at checkout. Order confirmation emails provide order details and tracking info. Customers have an account to view order history. The admin interface enables product and inventory management, order processing, customer service, marketing, and sales reporting. New arrivals and promotions incentivize repeat purchases. SEO, ads, and affiliate programs expand reach. Integrations with parts suppliers, drop shippers, and logistics services enable rapid scaling while minimizing overhead. Looking to challenge yourself or expand your portfolio? Check out our curated list of computer science project ideas to inspire your next groundbreaking project. Source Code: E-Commerce Website for Automotive Parts 4) Food delivery application This application should be able to form a bridge between restaurants and consumers. Restaurants owners must be able to sign up and list out their food items along with the price. Users must be able to sign up, view the restaurants nearby and order food items from selected restaurants. Restaurants should accept the order and assign a delivery person to the order. The location of the delivery person and the dynamic ETA of delivery must be displayed to the user who ordered food. The cart and payment page must be unique across the full application.  upGrad’s Exclusive Software and Tech Webinar for you – SAAS Business – What is So Different? document.createElement('video'); https://cdn.upgrad.com/blog/mausmi-ambastha.mp4 Additional features could include parts recommendation engines, vehicle fitment lookup, custom packaging, loyalty programs, and auto-replenishment. The focus is on providing automotive parts buyers with an intuitive, tailored e-commerce experience. The app can include cuisine browsing, personalized recommendations, ratings/reviews, and dish photos. Restaurants manage menus, availability, pricing, and order processing through a dashboard. Customers can save delivery addresses, payment methods, and favourite/recent orders. Once an order is placed, the restaurant receives the order with customer details. The restaurant confirms the order receipt and prep time. When ready, a delivery driver is assigned for pickup. Integrate with mapping APIs to track driver location and optimize routes. Push notifications update customers on order status. The delivery driver can mark orders picked up and dropped off within the app. Customers pay online or via cash. Ratings help restaurants and drivers improve service. Analytics provide insights on dishes, customers, and geography to inform marketing and operations. Source Code: Food delivery application 5) Grocery delivery application Assume this project is for a huge online departmental store. Assume that they have a myriad of grocery items at their godown. All items must be listed on the website, along with their quantities and prices. Users must be able to sign up and purchase groceries. The system should present him with delivery slot options, and the user must be able to choose his preferred slot. Users must then be taken to the payment page where he makes the payment with his favourite method.  In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses Additional features could include parts recommendation engines, vehicle fitment lookup, custom packaging, loyalty programs, and auto-replenishment. The focus is on providing automotive parts buyers with an intuitive, tailored e-commerce experience. The app can include cuisine browsing, personalized recommendations, ratings/reviews, and dish photos. Restaurants manage menus, availability, pricing, and order processing through a dashboard. Customers can save delivery addresses, payment methods, and favourite/recent orders. Once an order is placed, the restaurant receives the order with customer details. The restaurant confirms the order receipt and prep time. When ready, a delivery driver is assigned for pickup. Integrate with mapping APIs to track driver location and optimize routes. Push notifications update customers on order status. The delivery driver can mark orders picked up and dropped off within the app. Customers pay online or via cash. Ratings help restaurants and drivers improve service. Analytics provide insights on dishes, customers, and geography to inform marketing and operations. Source Code: Grocery delivery application 6) e-commerce portal for used furniture sales Another big example of full stack web app development project ideas for students is creating an e-commerce portal. Assume this project is for a startup that is acquiring used furniture from users at a price, refurbishing them and selling them off at a margin. The website must display second-hand furniture that is currently being sold. Users must be able to sign up on the site and set up their profile. Users must be able to search for their required products and checkout to the payment page. Once payment is successful, the expected time of product arrival must be communicated to the user via email as well as displayed on the order page. Users must also be able to sell used furniture to the company. Users must be able to upload pictures of the items they intend to sell. Based on the images, company admins must be able to decide whether to buy or not. Source Code: E-Commerce Portal for used Furniture Sales Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript Check out upGrad’s Full Stack Development Bootcamp 7) Web portal for motor servicing at home This project is going to be for an automotive workshop that is intending to deliver doorstep service. The workshop must be able to display their services and cost on the website. Users must be able to register and login to cart the required services. Users must then be able to confirm the service time slot and complete the checkout process. The mern project ideas site or mern stack project ideas lists the workshop’s offerings, such as oil changes, tire rotations, brake jobs, inspections, engine work, detailing, and more. Customers input their vehicle info to see applicable services and pricing. A shopping cart saves selected services, and a calendar displays available 2-hour appointment windows for at-home service. After selecting a time slot, customers enter payment and vehicle/location details. The workshop receives the service order and confirms via email and text. Customers are notified when the technician is en route with an ETA based on traffic. The technician can access service orders on a mobile app. Required parts and tools are loaded onto the vehicle beforehand. Customers pay any balance due upon completion. Email receipts summarize services rendered and parts replaced. The workshop manager assigns technicians and monitors schedules via a dashboard. Customer satisfaction ratings enable continual improvement of technicians and services. Marketing tools help acquire new customers in targeted geographies. Additional features could include: On-demand emergency roadside assistance. Fleet servicing. Maintenance reminder alerts for customers. Integration with spare parts inventory. The focus is on providing maximum convenience and transparency for at-home auto service. Source Code: Web portal for motor servicing at home 8) Project Management application This is going to be the toughest of all with a lot of features. The should have a framework of a basic social media site with users being able to communicate with each other. Users should be able to create projects and tasks within projects. Users must be able to assign tasks to other users and must be able to comment on it just like on a social media post. To start with, each user can have a calendar view and a kanban style board. Users must be able to close and archive tasks as well as projects when completed. Read our Popular Articles related to Software Development Why Learn to Code? How Learn to Code? How to Install Specific Version of NPM Package? Types of Inheritance in C++ What Should You Know? Adding one more easy and hassle-free idea to this list of full stack project ideas for resume. Source Code: Project Management application 9) To-do list project A to-do list app is a fundamental and straightforward project with a use case in daily life. One of the most common full-stack projects for beginners is a to-do list. Like Microsoft’s to-do list application, you can create a to-do list. When a task is finished, the feature to remove it from the list must also be available. Your front-end development skills will improve due to working on this project. You’ll gain valuable experience using the CRUD operations on databases by storing items in the directory and erasing them from it. You can also implement user login and authentication using the to-do list app. Below is a link to a sample source code for a to-do list website. You are welcome to draw ideas from it and create an amazing to-do list using your own talents and creativity. Source Code: To-do list project Advanced full stack project ideas for resume While working on full stack web app ideas for beginners will strengthen your base, practising on full stack web development project ideas for final year students will further enable your skills to shine brighter. Here are a few other full stack application examples and ideas to build your portfolio. 10) Blog Website and App One of the best advanced full stack project ideas for your resume is to create a website. Users can post their opinions on a variety of topics on a blog website. You can be as imaginative as you like. There are a huge number of blog websites. Any of these blog websites can serve as inspiration for your own. People must use their login credentials to access this site, and proper authentication will also be performed. The user can then publish their blogs for viewing by the public, and they should be saved in the database, so they stay there. The ability to edit a blog post after it has been published and delete it entirely from the post would be the icing on the cake. Source Code: Blog Website and App 11) Portfolio Website In the modern world, portfolio websites are a trendy concept. Developers create some amazing portfolio websites to impress clients and showcase their abilities. Making a portfolio website is a great practice, especially for front-end work, and there are no restrictions for students or even professionals having to learn web development. You can be as imaginative as you like. These full stack web development project ideas for students will allow them to not only present their own portfolio but flaunt their practical implementation, too, with a smooth interface. A developer portfolio site is a chance to highlight your best work and skills in a live setting. The homepage can include a bio, skills overview, and featured projects. Each project can have its page detailing the problem, technologies used, images, and results. Blog posts help demonstrate communication abilities along with full stack projects with source code. The site design itself acts as a showcase of front-end abilities with HTML, CSS, and JavaScript be it java full stack projects. A custom design system, animations, interactions, and responsive layout strengthen the presentation. The backend can utilize frameworks like Node, Django, or Ruby on Rails to serve content. Portfolios of full stack coding project ideas for final year students provide insights into coding style through tidy, commented code on GitHub. Integrations with services like LinkedIn and Twitter expand reach. Analytics provide data on visitor demographics, engagement, and conversions. The site can be continuously improved over time as new projects are completed. Version control makes iterating easy. Automated testing and performance monitoring ensure a smooth experience. Dynamic content allows customization for different audiences. The result is an ever-evolving representation of a developer’s skills, abilities, and growth. A portfolio site empowers you to put your best work on display for career opportunities or freelance clients. Source Code: Portfolio Website 12) Food delivery app/website Who is not a fan of food? After a long day of work, everyone wants to indulge in a delicious meal. As a result, many websites and apps, including Uber-eats, Swiggy, and Zomato in India, have become well-known and built profitable businesses around this concept. Therefore, a popular and relatively new idea for a full-stack project is a food application or website. Such full stack web development projects, if implemented successfully, can significantly gain popularity among the audience.  A food ordering and delivery platform connects customers, restaurants, and drivers for seamless meals on demand. Customers can browse local restaurants, menus, reviews, photos, and deals. A persistent cart allows ordering from multiple places in one checkout. Restaurants manage dynamic menus, availability, pricing, and order management via a dashboard. The order is assigned to a driver for pickup and delivery based on location and volume. Integrations with mapping and payment APIs enable optimized routes, ETAs, and cashless transactions. Customers can save delivery addresses and payment methods for faster repeat orders. Rating systems help restaurants and drivers improve service quality. Customer support tools facilitate refunds, cancellations, and issue resolution. Marketing features like promotions and partnerships drive acquisition. Backend databases maintain the menu, customer, restaurant, driver, and order data. Machine learning algorithms optimize driver dispatch and delivery times over time. Granular analytics provide insights to improve operations and marketing. The result is a scalable platform connecting hungry customers with their favourite local eateries via speedy delivery. Features like group ordering, self-service kiosks, and loyalty programs provide further engagement. Source Code: Food delivery app/website 13) Website or app for e-commerce Because it is a very well-known project, you can find an e-commerce website or app in almost every full-stack developer’s portfolio. This project is huge and calls for a great deal of database, front-end, and back-end expertise. It requires a lot of effort and time to complete and is considered a major project. Either create your own e-commerce website or app or attempt to copy an already successful, widely used app or website, such as Amazon, Flipkart, etc. Make sure to brainstorm diverse full stack web app ideas for e-commerce platforms. Source Code: Website or app for e-commerce  14) Video Conferencing App/Website Try to work on the most in-demand full stack web development projects to keep up with the changing demands of the time, and what’s better than the most popular video conferencing applications! The websites and apps for video conferencing are also excellent full-stack projects to get your hands on. Video conferencing tools like Zoom, Google-Meet, Microsoft Teams, and others have become indispensable in our lives since the global pandemic hit. A video conferencing app may have features like audio-video chat, text chat, video recording and storage for later use, call recording and chat storage, a whiteboard for drawing and explanations, and more. In this project, there is a lot to integrate and discover. Source Code: Video Conferencing App/Website 15) Social Media App/Website Another full stack application example is a social media app. In today’s world, social networking is all that is around us. We use numerous social media platforms on a daily basis, including Instagram, Facebook, Snapchat, and others. Making your own social media application is a fantastic full-stack project. A social media site or app is different from a chat app. An image, video, or text can be posted here for others to like, dislike, comment on, and share. It is comparable to creating a social network. This project is excellent for practising both front-end and back-end code (along with the database). The platform lets users sign up for accounts, create profiles, and connect as friends. The news feed shows posts from friends in chronological order. Users can create posts with text, images, videos, links, events, polls, etc. Likes, comments, shares, and reactions create engagement. Profiles, followers, tags, and discover features enable connections. Private messaging provides one-to-one and group chats. Push notifications alert users to new interactions. Moderation tools combat abuse. Analytical dashboards track growth, engagement, ads, and user demographics. APIs allow integration with other apps and embedding of social features. Additional capabilities could include live streaming, stories, influence scores, groups, events, marketplaces, and augmented reality. The focus is cultivating an active user community that provides entertainment, connection, and value at scale. Source Code: Social Media App/Website 16) Content Management Tool or System for Blogs Another good example of advanced full stack project ideas for your resume is creating a CMS. A good example of a content management system is WordPress. The user can drag and drop the available items to build a web page. An uncommon project like that attests to your full-stack developer expertise. Users of a Content Management System (CMS) must be able to drag and drop elements to build their own web pages. The user should be able to add text and media content into placeholders attached to the web page by using these features. Therefore, users should be able to create websites and post blogs. A text editor that accepts user input converts it to HTML and pushes it to the database. Source Code: Content Management Tool or System for Blogs 17) Project Management Tool The Project Management tool is the most difficult full-stack project and has many features. Examples include the Kissflow Project, Asana, and Trello. This project must have the structure of a fundamental social media platform with user-to-user communication. Users should be able to collaborate on project creation and create tasks inside of projects. The users should be able to allocate work to one another and comment on them, just like on social media. The tool allows teams to collaboratively plan projects, break down work into tasks, assign tasks, set due dates, track progress, and communicate. Robust permissions allow managers to restrict access as needed. Each project gets its dashboard for an overview and task management. Tasks can be categorized, tagged, prioritized, and assigned to team members. Due dates keep work on schedule. File attachments, comments, and activity feeds facilitate discussion of work. Integrations with calendars, email, and other tools sync across apps. Managers can view project health metrics and task completion status. Analytics provide insights into team productivity over time. Customizable workflows automate repetitive processes. API access enables integration with other systems. Additional features include time tracking, expense reporting, resource management, GANTT charts, budgeting, invoicing, and billing. The focus is on providing the features and flexibility to manage projects and tasks across any team, process, or enterprise. Custom branding and white-labeling make it easy to embed the tool across organizations. Source Code: Project Management Tool Conclusion Being a full stack developer is a tough job & that’s an important reason full stack developers get very good salary package. Its difficult but it’s achievable if you do the right amount of hard work. Execute these project ideas using different technologies and frameworks, and you will have hands-on experience in all underlying technologies. Make sure not to reuse the same language, database or framework over and over again on all projects. We hope you will have an excellent learning opportunity in executing these projects. If you are interested to learn more and need mentorship from industry experts, check out upGrad & IIIT Banglore’s PG Diploma in Full-Stack Software Development.

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Big Data Project Ideas Big Data is an exciting subject. It helps you find patterns and results you wouldn’t have noticed otherwise. This skill highly in demand, and you can quickly advance your career by learning it. So, if you are a big data beginner, the best thing you can do is work on some big data project ideas. But it can be difficult for a beginner to find suitable big data topics as they aren’t very familiar with the subject.  We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting big data project ideas which beginners can work on to put their big data knowledge to test. In this article, you will find top big data project ideas for beginners to get hands-on experience on big data Check out our free courses to get an edge over the competition. However, knowing the theory of big data alone won’t help you much. You’ll need to practice what you’ve learned. But how would you do that? You can practice your big data skills on big data projects. Projects are a great way to test your skills. They are also great for your CV. Especially big data research projects and data processing projects are something that will help you understand the whole of the subject most efficiently.  Read: Big data career path You won’t belive how this Program Changed the Career of Students Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses What are the areas where big data analytics is used? Before jumping into the list of  big data topics that you can try out as a beginner, you need to understand the areas of application of the subject. This will help you invent your own topics for data processing projects once you complete a few from the list. Hence, let’s see what are the areas where big data analytics is used the most. This will help you navigate how to identify issues in certain industries and how they can be resolved with the help of big data as big data research projects. Banking and Safety: The banking industry often deals with cases of card fraud, security fraud, ticks and such other issues that greatly hamper their functioning as well as market reputation. Hence to tackle that, the securities exchange commission aka SEC takes the help of big data and monitors the financial market activity.  This has further helped them manage a safer environment for highly valuable customers like retail traders, hedge funds, big banks and other eminent individuals in the financial market. Big data has helped this industry in the cases like anti-money laundering, fraud mitigation, demand enterprise risk management and other cases of risk analytics.  Media and Entertainment industry It is needless to say that the media and entertainment industry heavily depends on the verdict of the consumers and this is why they are always required to put up their best game. For that, they require to understand the current trends and demands of the public, which is also something that changes rapidly these days. To get an in-depth understanding of consumer behaviour and their needs, the media and entertainment industry collects, analyses and utilises customer insights. They leverage mobile and social media content to understand the patterns at a real-time speed.  The industry leverages Big data to run detailed sentiment analysis to pitch the perfect content to the users. Some of the biggest names in the entertainment industry such as Spotify and Amazon Prime are known for using big data to provide accurate content recommendations to their users, which helps them improve their customer satisfaction and, therefore, increases customer retention.  Healthcare Industry Even though the healthcare industry generates huge volumes of data on a daily basis which can be ustilised in many ways to improve the healthcare industry, it fails to utilise it completely due to issues of usability of it. Yet there is a significant number of areas where the healthcare industry is continuously utilising Big Data. The main area where the healthcare industry is actively leveraging big data is to improve hospital administration so that patients can revoke best-in-class clinical support. Apart from that, Big Data is also used in fighting lethal diseases like cancer. Big Data has also helped the industry to save itself from potential frauds and committing usual man-made errors like providing the wrong dosage, medicine etc.  Education Similar to the society that we live in, the education system is also evolving. Especially after the pandemic hit hard, the change became even more rapid. With the introduction of remote learning, the education system transformed drastically, and so did its problems. On that note, Big Data significantly came in handy, as it helped educational institutions to get the insights that can be used to take the right decisions suitable for the circumstances. Big Data helped educators to understand the importance of creating a unique and customised curriculum to fight issues like students not being able to retain attention.  It not only helped improve the educational system but to identify the student’s strengths and channeled them right.  Government and Public Services Likewise the field of government and public services itself, the applications of Big Data by them are also extensive and diverse. Government leverages big data mostly in areas like financial market analysis, fraud detection, energy resource exploration, environment protection, public-health-related research and so forth.  The Food and Drug Administration (FDA) actively uses Big Data to study food-related illnesses and disease patterns.  Retail and Wholesale Industry In spite of having tons of data available online in form of reviews, customer loyalty cards, RFID etc. the retail and wholesale industry is still lacking in making complete use of it. These insights hold great potential to change the game of customer experience and customer loyalty.  Especially after the emergence of e-commerce, big data is used by companies to create custom recommendations based on their previous purchasing behaviour or even from their search history.  In the case of brick-and-mortar stores as well, big data is used for monitoring store-level demand in real-time so that it can be ensured that the best-selling items remain in stock. Along with that, in the case of this industry, data is also helpful in improving the entire value chain to increase profits.   Manufacturing and Resources Industry The demand for resources of every kind and manufactured product is only increasing with time which is making it difficult for industries to cope. However, there are large volumes of data from these industries that are untapped and hold the potential to make both industries more efficient, profitable and manageable.  By integrating large volumes of geospatial and geographical data available online, better predictive analysis can be done to find the best areas for natural resource explorations. Similarly, in the case of the manufacturing industry, Big Data can help solve several issues regarding the supply chain and provide companies with a competitive edge.  Insurance Industry  The insurance industry is anticipated to be the highest profit-making industry but its vast and diverse customer base makes it difficult for it to incorporate state-of-the-art requirements like personalized services, personalised prices and targeted services. To tackle these prime challenges Big Data plays a huge part. Big data helps this industry to gain customer insights that further help in curating simple and transparent products that match the recruitment of the customers. Along with that, big data also helps the industry analyse and predict customer behaviours and results in the best decision-making for insurance companies. Apart from predictive analytics, big data is also utilised in fraud detection.  How do you create a big data project? Creating a big data project involves several key steps and considerations. Here’s a general outline to guide you through the process: Define Objectives: Clearly define the objectives and goals of your big data project. Identify the business problems you want to solve or the insights you aim to gain from the data. Data Collection: Determine the sources of data you need for your project. It could be structured data from databases, unstructured data from social media or text documents, or semi-structured data from log files or XML. Plan how you will collect and store this data. Data Storage: Choose a suitable storage solution for your data. Depending on the volume and variety of data, you may consider traditional databases, data lakes, or distributed file systems like Hadoop HDFS. Data Processing: Determine how you will process and manage your big data. This step usually involves data cleaning, transformation, and integration. Technologies like Apache Spark or Apache Hadoop MapReduce are commonly used for large-scale data processing. Data Analysis: Perform exploratory data analysis to gain insights and understand patterns within the data. Use data visualization tools to present the findings. Implement Algorithms: If your project involves machine learning or advanced analytics, implement relevant algorithms to extract meaningful information from the data. Performance Optimization: Big data projects often face performance challenges. Optimize your data processing pipelines, algorithms, and infrastructure for efficiency and scalability. Data Security and Privacy: Ensure that your project adheres to data security and privacy regulations. Implement proper data access controls and anonymization techniques if needed. Deploy and Monitor: Deploy your big data project in a production environment and set up monitoring to track its performance and identify any issues. Evaluate Results: Continuously evaluate the results of your big data project against the defined objectives. Refine and improve your approach based on feedback and insights gained from the project. Documentation: Thoroughly document each step of the project, including data sources, data processing steps, analysis methodologies, and algorithms used. This documentation will be valuable for future reference and for collaborating with others. Team Collaboration: Big data projects often involve collaboration between various teams, such as data engineers, data scientists, domain experts, and IT professionals. Effective communication and collaboration are crucial for the success of the project. The Key Elements of a Good Big Data Project Before you learn about different big data projects, you should understand the criteria for evaluating them: Quality Over Quantity In the field of big data, it is a common tendency to prioritize quantity. However, quality should be a major focus while selecting data to analyze. The ultimate goal of big data analysis is nothing different from other analytical tasks. It involves driving important insights to fulfill business objectives and make major decisions. So, it’s extremely crucial to collect data from the right sources for analysis. You can explore different resources before finding the absolute best for collecting data. Additionally, you will have to find the right algorithms for processing data and interpreting everything accurately. Concentrate on Outcome and Impact The purpose of big data projects is to meet several business objectives. So, your focus shouldn’t be on using more data or utilizing more tools to perform big data analysis. Instead, you should improve the impact of big data projects to allow organizations to develop better strategies. Clean Code and Analysis This aspect of big data projects will depend on your work mechanism as an individual or a team. It’s extremely vital to generate clean code. Therefore, your code should be formatted in the right way and contain comments in the necessary places. A clean code makes it easy to proceed with big data projects. Even your colleagues will find it easier to proceed with the project at a later point when you might not be available. While writing code for data analysis, rely on fair and goal-oriented methodologies. Emotions and biases can easily mess with the accuracy of your data analysis. So, you should stay away from these mistakes while writing code for big data projects. What problems you might face in doing Big Data Projects Big data is present in numerous industries. So you’ll find a wide variety of big data project topics to work on too. Apart from the wide variety of project ideas, there are a bunch of challenges a big data analyst faces while working on such projects. They are the following: Limited Monitoring Solutions You can face problems while monitoring real-time environments because there aren’t many solutions available for this purpose. That’s why you should be familiar with the technologies you’ll need to use in big data analysis before you begin working on a project. Timing Issues A common problem among data analysis is of output latency during data virtualization. Most of these tools require high-level performance, which leads to these latency problems. Due to the latency in output generation, timing issues arise with the virtualization of data. The requirement of High-level Scripting When working on big data analytics projects, you might encounter tools or problems which require higher-level scripting than you’re familiar with. In that case, you should try to learn more about the problem and ask others about the same. Data Privacy and Security While working on the data available to you, you have to ensure that all the data remains secure and private. Leakage of data can wreak havoc to your project as well as your work. Sometimes users leak data too, so you have to keep that in mind. Knowledge Read: Big data jobs & Career planning Unavailability of Tools You can’t do end-to-end testing with just one tool. You should figure out which tools you will need to use to complete a specific project. When you don’t have the right tool at a specific device, it can waste a lot of time and cause a lot of frustration. That is why you should have the required tools before you start the project. Check out big data certifications at upGrad Too Big Datasets You can come across a dataset which is too big for you to handle. Or, you might need to verify more data to complete the project as well. Make sure that you update your data regularly to solve this problem. It’s also possible that your data has duplicates, so you should remove them, as well. While working on big data projects, keep in mind the following points to solve these challenges:         Use the right combination of hardware as well as software tools to make sure your work doesn’t get hampered later on due to the lack of the same.         Check your data thoroughly and get rid of any duplicates.         Follow Machine Learning approaches for better efficiency and results.         What are the technologies you’ll need to use in Big Data Analytics Projects: We recommend the following technologies for beginner-level big data projects:         Open-source databases         C++, Python         Cloud solutions (such as Azure and AWS)         SAS         R (programming language)         Tableau         PHP and Javascript Each of these technologies will help you with a different sector. For example, you will need to use cloud solutions for data storage and access. On the other hand, you will need to use R for using data science tools. These are all the problems you need to face and fix when you work on big data project ideas.  If you are not familiar with any of the technologies we mentioned above, you should learn about the same before working on a project. The more big data project ideas you try, the more experience you gain. Otherwise, you’d be prone to making a lot of mistakes which you could’ve easily avoided. So, here are a few Big Data Project ideas which beginners can work on: Read: Career in big data and its scope. Big Data Project Ideas: Beginners Level This list of big data project ideas for students is suited for beginners, and those just starting out with big data. These big data project ideas will get you going with all the practicalities you need to succeed in your career as a big data developer. Further, if you’re looking for big data project ideas for final year, this list should get you going. So, without further ado, let’s jump straight into some big data project ideas with source code that will strengthen your base and allow you to climb up the ladder. We know how challenging it is to find the right project ideas as a beginner. You don’t know what you should be working on, and you don’t see how it will benefit you. That’s why we have prepared the following list of big data projects with source code so you can start working on them: Let’s start with big data project ideas. Fun Big Data Project Ideas Social Media Trend Analysis: Gather data from various platforms and analyze trends, topics, and sentiment. Music Recommender System: Build a personalized music recommendation engine based on user preferences. Video Game Analytics: Analyze gaming data to identify patterns and player behavior. Real-time Traffic Analysis: Use data to create visualizations and optimize traffic routes. Energy Consumption Optimization: Analyze energy usage data to propose energy-saving strategies. Predicting Box Office Success: Develop a model to predict movie success based on various factors. Food Recipe Recommendation: Recommend recipes based on dietary preferences and history. Wildlife Tracking and Conservation: Use big data to track and monitor wildlife for conservation efforts. Fashion Trend Analysis: Analyze fashion data to identify trends and popular styles. Online Gaming Community Analysis: Understand player behavior and social interactions in gaming communities. Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript 1. Classify 1994 Census Income Data One of the best ideas to start experimenting you hands-on big data projects for students is working on this project. You will have to build a model to predict if the income of an individual in the US is more or less than $50,000 based on the data available. A person’s income depends on a lot of factors, and you’ll have to take into account every one of them. Source Code: Classify 1994 Census Income Data 2. Analyze Crime Rates in Chicago Law enforcement agencies take the help of big data to find patterns in the crimes taking place. Doing this helps the agencies in predicting future events and helps them in mitigating the crime rates. You will have to find patterns, create models, and then validate your model. Source Code: Analyze Crime Rates in Chicago 3. Text Mining Project This is one of the excellent deep learning project ideas for beginners. Text mining is in high demand, and it will help you a lot in showcasing your strengths as a data scientist. In this project, you will have to perform text analysis and visualization of the provided documents.   You will have to use Natural Language Process Techniques for this task. Source Code: Text Mining Project In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses Big Data Project Ideas: Advanced Level 4. Big Data for cybersecurity This project will investigate the long-term and time-invariant dependence relationships in large volumes of data. The main aim of this Big Data project is to combat real-world cybersecurity problems by exploiting vulnerability disclosure trends with complex multivariate time series data. This cybersecurity project seeks to establish an innovative and robust statistical framework to help you gain an in-depth understanding of the disclosure dynamics and their intriguing dependence structures. Source Code: Big Data for cybersecurity 5. Health status prediction This is one of the interesting big data project ideas. This Big Data project is designed to predict the health status based on massive datasets. It will involve the creation of a machine learning model that can accurately classify users according to their health attributes to qualify them as having or not having heart diseases. Decision trees are the best machine learning method for classification, and hence, it is the ideal prediction tool for this project. The feature selection approach will help enhance the classification accuracy of the ML model. Source Code: Health status prediction 6. Anomaly detection in cloud servers In this project, an anomaly detection approach will be implemented for streaming large datasets. The proposed project will detect anomalies in cloud servers by leveraging two core algorithms – state summarization and novel nested-arc hidden semi-Markov model (NAHSMM). While state summarization will extract usage behaviour reflective states from raw sequences, NAHSMM will create an anomaly detection algorithm with a forensic module to obtain the normal behaviour threshold in the training phase. Source Code: Anomaly detection 7. Recruitment for Big Data job profiles Recruitment is a challenging job responsibility of the HR department of any company. Here, we’ll create a Big Data project that can analyze vast amounts of data gathered from real-world job posts published online. The project involves three steps: Identify four Big Data job families in the given dataset. Identify nine homogeneous groups of Big Data skills that are highly valued by companies.  Characterize each Big Data job family according to the level of competence required for each Big Data skill set. The goal of this project is to help the HR department find better recruitments for Big Data job roles. Source Code: Recruitment for Big Data job 8. Malicious user detection in Big Data collection This is one of the trending deep learning project ideas. When talking about Big Data collections, the trustworthiness (reliability) of users is of supreme importance. In this project, we will calculate the reliability factor of users in a given Big Data collection. To achieve this, the project will divide the trustworthiness into familiarity and similarity trustworthiness. Furthermore, it will divide all the participants into small groups according to the similarity trustworthiness factor and then calculate the trustworthiness of each group separately to reduce the computational complexity. This grouping strategy allows the project to represent the trust level of a particular group as a whole.  Source Code: Malicious user detection 9. Tourist behaviour analysis This is one of the excellent big data project ideas. This Big Data project is designed to analyze the tourist behaviour to identify tourists’ interests and most visited locations and accordingly, predict future tourism demands. The project involves four steps:  Textual metadata processing to extract a list of interest candidates from geotagged pictures.  Geographical data clustering to identify popular tourist locations for each of the identified tourist interests.  Representative photo identification for each tourist interest.  Time series modelling to construct a time series data by counting the number of tourists on a monthly basis.  Source Code: Tourist behaviour analysis 10. Credit Scoring This project seeks to explore the value of Big Data for credit scoring. The primary idea behind this project is to investigate the performance of both statistical and economic models. To do so, it will use a unique combination of datasets that contains call-detail records along with the credit and debit account information of customers for creating appropriate scorecards for credit card applicants. This will help to predict the creditworthiness of credit card applicants. Source Code: Credit Scoring 11. Electricity price forecasting This is one of the interesting big data project ideas. This project is explicitly designed to forecast electricity prices by leveraging Big Data sets. The model exploits the SVM classifier to predict the electricity price. However, during the training phase in SVM classification, the model will include even the irrelevant and redundant features which reduce its forecasting accuracy. To address this problem, we will use two methods – Grey Correlation Analysis (GCA) and Principle Component Analysis. These methods help select important features while eliminating all the unnecessary elements, thereby improving the classification accuracy of the model. Source Code: Electricity price forecasting 12. BusBeat BusBeat is an early event detection system that utilizes GPS trajectories of periodic-cars travelling routinely in an urban area. This project proposes data interpolation and the network-based event detection techniques to implement early event detection with GPS trajectory data successfully. The data interpolation technique helps to recover missing values in the GPS data using the primary feature of the periodic-cars, and the network analysis estimates an event venue location. Source Code: BusBeat 13. Yandex.Traffic Yandex.Traffic was born when Yandex decided to use its advanced data analysis skills to develop an app that can analyze information collected from multiple sources and display a real-time map of traffic conditions in a city. After collecting large volumes of data from disparate sources, Yandex.Traffic analyses the data to map accurate results on a particular city’s map via Yandex.Maps, Yandex’s web-based mapping service. Not just that, Yandex.Traffic can also calculate the average level of congestion on a scale of 0 to 10 for large cities with serious traffic jam issues. Yandex.Traffic sources information directly from those who create traffic to paint an accurate picture of traffic congestion in a city, thereby allowing drivers to help one another. Source Code: Yandex.Traffic Additional Topics         Predicting effective missing data by using Multivariable Time Series on Apache Spark         Confidentially preserving big data paradigm and detecting collaborative spam         Predict mixed type multi-outcome by using the paradigm in healthcare application         Use an innovative MapReduce mechanism and scale Big HDT Semantic Data Compression         Model medical texts for Distributed Representation (Skip Gram Approach based) Learn: Mapreduce in big data More Fun Big Data Projects Some more exciting big data projects to develop your skills include: Traffic Control Using Big Data Traffic issues are a common burden for many major cities, especially during peak hours. To address this problem, regularly monitoring popular and alternate routes for traffic may provide some relief. Leveraging the power of big data projects with real-time traffic simulation and predictions offers numerous advantages. In fact, this cutting-edge technology has already demonstrated success in effectively modeling traffic patterns. Take, for example, the Lambda Architecture program designed to tackle traffic challenges in Chicago. By tracking over 1,250 city roads, this program provides up-to-date information on traffic flow and traffic violations. Source Code: Traffic Control Using Big Data Search Engines Search engines manage trillions of network objects and track online user movements to decode their search requests. But how do search engines make sense of all this information? They do so by transforming the vast amount of website content into measurable data. This presents an exciting opportunity for curious newbies looking to delve into the world of big data projects and Hadoop. Specifically, they can hone their skills in querying and analyzing data with the help of Apache Hive. With its SQL-like interface, Hive offers a user-friendly way to access data from a variety of Hadoop-based databases. Anyone already familiar with SQL will find this project easy to complete. Source Code: Search Engines Medical Insurance Fraud Detection Medical insurance fraud detection is quite easy with cutting-edge data science methodologies. By leveraging real-time analysis and advanced classification algorithms, this approach can promote trust in the medical insurance industry. It is one of the big data projects that address the issue of healthcare costs alongside preventing fraud. This project harnesses the power of data analytics to uncover critical links between healthcare professionals. Source Code: Medical Insurance Fraud Detection Data Warehouse Design If you are interested in big data projects related to e-commerce sites, this one is recommended for you. Your task will be to construct a data warehouse for a retail enterprise. This project has a particular focus on optimizing pricing and inventory allocation. This project will help identify whether certain markets have an inclination toward high-priced products. Moreover, it will help you understand whether price adjustment or inventory redistribution is necessary according to locations. Get ready to harness the power of big data to uncover valuable insights in these areas. Source Code: Data Warehouse Design Recommendation System The vast world of online services offers access to an endless array of items. You will find music, video clips, and more. Big data can help create recommendation systems that will provide you with tailored suggestions. All big data projects analyze user data to effectively offer recommendations. They will consider browsing history and other metrics to come up with the right suggestions. In this specific big data project, you will have to leverage different recommendation models available on the Hadoop Framework. This will ensure that you understand which model will deliver optimal outcomes. Source Code: Recommendation System Wikipedia Trend Visualization Human brains get exposed to different formats of data. But our brains are programmed to understand visual data better than anything else. In fact, the brain can comprehend visual data within only 13 milliseconds. Wikipedia is a go-to destination for a vast number of individuals all over the world for research purposes or general knowledge. At times, people visit these pages out of pure curiosity. The endless amount of data within its pages can be harnessed and refined through the use of Hadoop. By utilizing Zeppelin notebooks, this data can then be transformed into visually appealing insights. This will enable a deeper understanding of trends and patterns across different demographics and parameters. Therefore, it is one of the best big data projects to understand the potential of visualization. Source Code: Wikipedia Trend Visualization Website Clickstream Data Visualization Clickstream data analysis is about understanding the web pages visited by a specific user. This type of analysis helps with web page marketing and product management. Moreover, clickstream data analysis can help with creating targeted advertisements. Users will always visit websites according to their interests and needs. So, clickstream analysis is all about figuring out what a user is on the lookout for. It is one of the big data projects that need the Hadoop framework. Source Code: Clickstream data analysis Image Caption Generation The growing influence of social media requires businesses to produce engaging content. Catchy images are definitely important on social media profiles. But businesses also need to add attractive captions to describe the images. With captions and useful hashtags, businesses are able to reach the intended target audience more easily. Producing relevant captions for images requires dealing with large datasets. Therefore, image caption generation can be one of the most interesting big data projects. This project involves processing images with the help of deep learning techniques. It helps in understanding the image and creating appealing captions with AI. Python is often the source code behind these big data projects. So, it is better to proceed with this project after working on something with Python as the source code. Source Code: Image Caption Generation GIS Analytics for Effective Waste Management Large amounts of waste pose a threat to the environment and our well-being. Proper waste management is necessary for addressing this issue. Waste management is not just about collecting unwanted items and their disposal. It also involves the transportation and recycling of waste. Waste management can be one of the most interesting big data projects by leveraging the power of GIS modeling. These models can help create a strategic path for collecting waste. Moreover, data experts can create routes to dispose of waste at designated areas like landfills or recycling centers. Additionally, these big data projects can help find ideal locations for landfills. These projects can also help with the proper placement of garbage bins all over the city. Source Code: Waste Management Network Traffic and Call Data Analysis The telecommunication industry produces heaps of data every day. But only a small amount of this data can be useful for improving business practices. The real challenge is in dealing with such vast volumes of data in real time. One of the most interesting big data projects is analyzing the data available in the telecommunications sector. It will help the telecom industry to undertake decisions regarding the improvement of customer experience. This big data project will involve analyzing the network traffic. As a result, it will become easier to address issues like network interruptions and call drops. By assessing the usage patterns of customers, telecom companies will be able to create better service plans. As a result, customers will be satisfied with plans that fulfill their overall needs. The tools used for this kind of big data project will depend on its complexity. Source Code: Network Traffic Fruit Image Classification This can be one of the most interesting big data projects with professionals working on a mobile application. It will be a mobile app capable of providing insights about fruit harvesting by analyzing different pictures. This project will involve leveraging AWS cloud tools to develop a data processing chain. Some steps in this chain will include dimensionality reduction and operating a fruit image classification engine. While working on this big data project, you will have to generate PySpark scripts. Your task will become easier with a big data architecture created on an EC2 Linux server. Due to its compatibility with AWS, DataBricks is also ideal for this project. Source Code: Fruit Image Classification Read our Popular Articles related to Software Development Why Learn to Code? How Learn to Code? How to Install Specific Version of NPM Package? Types of Inheritance in C++ What Should You Know? Conclusion In this article, we have covered top big data project ideas. We started with some beginner projects which you can solve with ease. Once you finish with these simple projects, I suggest you go back, learn a few more concepts and then try the intermediate projects. When you feel confident, you can then tackle the advanced projects. If you wish to improve your big data skills, you need to get your hands on these big data project ideas. Working on big data projects will help you find your strong and weak points. Completing these projects will give you real-life experience of working as a data scientist. If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore. Learn Software Development Courses online from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs or Masters Programs to fast-track your career.

by upGrad

29 May 2024

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Machine learning is the most algorithm-intense field in computer science. Gone are those days when people had to code all algorithms for machine learning. Thanks to Python and it’s libraries, modules, and frameworks. Python machine learning libraries have grown to become the most preferred language for machine learning algorithm implementations. Learning Python is essential to master data science and machine learning. Let’s have a look at the main Python libraries used for machine learning. Top Python Machine Learning Libraries 1) NumPy NumPy is a well known general-purpose array-processing package. An extensive collection of high complexity mathematical functions make NumPy powerful to process large multi-dimensional arrays and matrices. NumPy is very useful for handling linear algebra, Fourier transforms, and random numbers. Other libraries like TensorFlow uses NumPy at the backend for manipulating tensors. With NumPy, you can define arbitrary data types and easily integrate with most databases. NumPy can also serve as an efficient multi-dimensional container for any generic data that is in any datatype. The key features of NumPy include powerful N-dimensional array object, broadcasting functions, and out-of-box tools to integrate C/C++ and Fortran code. Its key features are as below: Supports n-dimensional arrays to enable vectorization, indexing, and broadcasting operations. Supports Fourier transforms mathematical functions, linear algebra methods, and random number generators. Implementable on different computing platforms, including distributed and GPU computing. Easy-to-use high-level syntax with the optimized Python code to provide high speed and flexibility. In addition to that, NumPy enables the numerical operations of plenty of libraries associated with data science, data visualization, image processing, quantum computing, signal processing, geographic processing, bioinformatics, etc. So, it is one of the versatile machine learning libraries. 2) SciPy With machine learning growing at supersonic speed, many Python developers were creating python libraries for machine learning, especially for scientific and analytical computing. Travis Oliphant, Eric Jones, and Pearu Peterson in 2001 decided to merge most of these bits and pieces codes and standardize it. The resulting library was then named as SciPy library.  The current development of the SciPy library is supported and sponsored by an open community of developers and distributed under the free BSD license. The SciPy library offers modules for linear algebra, image optimization, integration interpolation, special functions, Fast Fourier transform, signal and image processing, Ordinary Differential Equation (ODE) solving, and other computational tasks in science and analytics. The underlying data structure used by SciPy is a multi-dimensional array provided by the NumPy module. SciPy depends on NumPy for the array manipulation subroutines. The SciPy library was built to work with NumPy arrays along with providing user-friendly and efficient numerical functions. FYI: Free nlp course! One of the unique features of SciPy is that its functions are useful in maths and other sciences. Some of its extensively used functions are optimization functions, statistical functions, and signal processing. It supports functions for finding the numerical solute to integrals. So you can solve differential equations and optimization. The following areas of SciPy’s applications make it one of the popular machine learning libraries. Multidimensional image processing Solves Fourier transforms, and differential equations Its optimized algorithms help you to efficiently and reliably perform linear algebra calculations 3) Scikit-learn In 2007, David Cournapeau developed the Scikit-learn library as part of the Google Summer of Code project. In 2010 INRIA involved and did the public release in January 2010. Skikit-learn was built on top of two Python libraries – NumPy and SciPy and has become the most popular Python machine learning library for developing machine learning algorithms.   Scikit-learn has a wide range of supervised and unsupervised learning algorithms that works on a consistent interface in Python. The library can also be used for data-mining and data analysis. The main machine learning functions that the Scikit-learn library can handle are classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. Many ML enthusiasts and data scientists use scikit-learn in their AI journey. Essentially, it is an all-inclusive machine learning framework. Occasionally, many people overlook it because of the prevalence of more cutting-edge Python libraries and frameworks. However, it is still a powerful library and efficiently solves complex Machine Learning tasks. The following features of scikit-learn make it one of the best machine learning libraries in Python: Easy to use for precise predictive data analysis Simplifies solving complex ML problems like classification, preprocessing, clustering, regression, model selection, and dimensionality reduction Plenty of inbuilt machine learning algorithms Helps build a fundamental to advanced level ML model Developed on top of prevalent libraries like SciPy, NumPy, and Matplotlib Our learners also read – python online course free! 4) Theano Theano is a python machine learning library that can act as an optimizing compiler for evaluating and manipulating mathematical expressions and matrix calculations. Built on NumPy, Theano exhibits a tight integration with NumPy and has a very similar interface. Theano can work on Graphics Processing Unit (GPU) and CPU. Working on GPU architecture yields faster results. Theano can perform data-intensive computations up to 140x faster on GPU than on a CPU. Theano can automatically avoid errors and bugs when dealing with logarithmic and exponential functions. Theano has built-in tools for unit-testing and validation, thereby avoiding bugs and problems.  Theano’s fast speeds give a competitive edge to C projects for problem-solving tasks that involve huge amounts of data. It makes most GPUs perform better than C language on a CPU. It efficiently accepts structures and transforms them into extremely efficient code which uses NumPy and a few native libraries. Primarily, it is designed to deal with various computations demanded by huge neural network algorithms utilized in Deep Learning. Therefore, it is one of the popular machine learning libraries in Python, as well as deep learning. Here are some prominent benefits of using Theano: Stability Optimization: It can determine some unsteady expressions and can use steadier expressions to solve them 2. Execution Speed Optimization: It uses the latest GPUs and implements parts of expressions in your GPU or CPU. So, it is faster than Python.    3. Symbolic Differentiation: It automatically creates symbolic graphs for computing gradients. Also, Check out all Trending Python Tutorial Concepts in 2024. 5) TensorFlow TensorFlow was developed for Google’s internal use by the Google Brain team. Its first release came in November 2015 under Apache License 2.0. TensorFlow is a popular computational framework for creating machine learning models. TensorFlow supports a variety of different toolkits for constructing models at varying levels of abstraction. TensorFlow exposes a very stable Python and C++ APIs. It can expose, backward compatible APIs for other languages too, but they might be unstable. TensorFlow has a flexible architecture with which it can run on a variety of computational platforms CPUs, GPUs, and TPUs. TPU stands for Tensor processing unit, a hardware chip built around TensorFlow for machine learning and artificial intelligence. TensorFlow empowers some of the largest contemporary AI models globally. Alternatively, it is recognized as an end-to-end Deep Learning and Machine Learning library to solve practical challenges. The following key features of TensorFlow make it one of the best machine learning libraries Python: Comprehensive control on developing a machine learning model and robust neural network Deploy models on cloud, web, mobile, or edge devices through TFX, TensorFlow.js, and TensorFlow Lite Supports abundant extensions and libraries for solving complex problems Supports different tools for integration of Responsible AI and ML solutions Hope the Above Top 5 machine learning libraries in Python are clear, lets look at the other list of python libraries for machine learning. 6) Keras Keras has over 200,000 users as of November 2017. Keras is an open-source library used for neural networks and machine learning. Keras can run on top of TensorFlow, Theano, Microsoft Cognitive Toolkit, R, or PlaidML. Keras also can run efficiently on CPU and GPU.  Keras works with neural-network building blocks like layers, objectives, activation functions, and optimizers. Keras also have a bunch of features to work on images and text images that comes handy when writing Deep Neural Network code. Apart from the standard neural network, Keras supports convolutional and recurrent neural networks.  It was released in 2015 and by now, it is a cutting-edge open-source Python deep learning framework and API. It is identical to Tensorflow in several aspects. But it is designed with a human-based approach to make DL and ML accessible and easy for everybody. You can conclude that Keras is one of the versatile machine learning libraries Python because it includes: Everything that TensorFlow provides but presents in easy to understand format. Quickly runs various DL iterations with full deployment proficiencies. Support large TPUs and GPU clusters which facilitate commercial Python machine learning. It is used in various applications, including natural language processing, computer vision, reinforcement learning, and generative deep learning. So, it is useful for graph, structured, audio, and time series data. Best Machine Learning and AI Courses Online Master of Science in Machine Learning & AI from LJMU Executive Post Graduate Programme in Machine Learning & AI from IIITB Advanced Certificate Programme in Machine Learning & NLP from IIITB Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland To Explore all our courses, visit our page below. Machine Learning Courses 7) PyTorch PyTorch has a range of tools and libraries that support computer vision, machine learning, and natural language processing. The PyTorch library is open-source and is based on the Torch library. The most significant advantage of PyTorch library is it’s ease of learning and using. PyTorch can smoothly integrate with the python data science stack, including NumPy. You will hardly make out a difference between NumPy and PyTorch. PyTorch also allows developers to perform computations on Tensors. PyTorch has a robust framework to build computational graphs on the go and even change them in runtime. Other advantages of PyTorch include multi GPU support, simplified preprocessors, and custom data loaders.  Facebook released PyTorch as a powerful competitor of TensorFlow in 2016. It has now attained huge popularity among deep learning and machine learning researchers. Various aspects of PyTorch suggest that it is one of the outstanding and best Python libraries for machine learning. Here are some of its key capabilities. Fully support the development of customized deep neural networks Production-ready with TorchServe Supports distributed computing through the torch.distributed backend Supports various extensions and tools to solve complex problems Compatible on all leading cloud platforms for extensible deployment Also supported on GitHub as an open-source Python framework 8) Pandas Pandas are turning up to be the most popular Python library that is used for data analysis with support for fast, flexible, and expressive data structures designed to work on both “relational” or “labeled” data. Pandas today is an inevitable library for solving practical, real-world data analysis in Python. Pandas is highly stable, providing highly optimized performance. The backend code is purely written in C or Python.  The two main types of data structures used by pandas are : Series (1-dimensional) DataFrame (2-dimensional) These two put together can handle a vast majority of data requirements and use cases from most sectors like science, statistics, social, finance, and of course, analytics and other areas of engineering.  Pandas support and perform well with different kinds of data including the below : Tabular data with columns of heterogeneous data. For instance, consider the data coming from the SQL table or Excel spreadsheet. Ordered and unordered time series data. The frequency of time series need not be fixed, unlike other libraries and tools. Pandas is exceptionally robust in handling uneven time-series data Arbitrary matrix data with the homogeneous or heterogeneous type of data in the rows and columns Any other form of statistical or observational data sets. The data need not be labeled at all. Pandas data structure can process it even without labeling.  It was launched as an open-source Python library in 2009. Currently, it has become one of the favourite Python libraries for machine learning among many ML enthusiasts. The reason is it offers some robust techniques for data analysis and data manipulation. This library is extensively used in academia. Moreover, it supports different commercial domains like business and web analytics, economics, statistics, neuroscience, finance, advertising, etc. It also works as a foundational library for many advanced Python libraries. Here are some of its key features: Handles missing data Handles time series data Supports indexing, slicing, reshaping, subsetting, joining, and merging of large datasets Offers optimized code for Python using C and Cython Powerful DataFrame object for broad data manipulation support In-demand Machine Learning Skills Artificial Intelligence Courses Tableau Courses NLP Courses Deep Learning Courses 9) Matplotlib Matplotlib is a data visualization library that is used for 2D plotting to produce publication-quality image plots and figures in a variety of formats. The library helps to generate histograms, plots, error charts, scatter plots, bar charts with just a few lines of code. It provides a MATLAB-like interface and is exceptionally user-friendly. It works by using standard GUI toolkits like GTK+, wxPython, Tkinter, or Qt to provide an object-oriented API that helps programmers to embed graphs and plots into their applications.  It is the oldest Python machine learning library. However, it is still not obsolete. It is one of the most innovative data visualization libraries for Python. So, the ML community admires it. The following features of the Matplotlib library make it a famous Python machine learning among the ML community: Its interactive charts and plots allow fascinating data storytelling Offers an extensive list of plots appropriate for a particular use case Charts and plots are customizable and exportable to various file formats Offers embeddable visualizations with different GUI applications Various Python frameworks and libraries extend Matplotlib Join the Machine Learning Course online from the World’s top Universities – Masters, Executive Post Graduate Programs, and Advanced Certificate Program in ML & AI to fast-track your career. Popular AI and ML Blogs & Free Courses IoT: History, Present & Future Machine Learning Tutorial: Learn ML What is Algorithm? Simple & Easy Robotics Engineer Salary in India : All Roles A Day in the Life of a Machine Learning Engineer: What do they do? What is IoT (Internet of Things) Permutation vs Combination: Difference between Permutation and Combination Top 7 Trends in Artificial Intelligence & Machine Learning Machine Learning with R: Everything You Need to Know AI & ML Free Courses Introduction to NLP Fundamentals of Deep Learning of Neural Networks Linear Regression: Step by Step Guide Artificial Intelligence in the Real World Introduction to Tableau Case Study using Python, SQL and Tableau Why Python library used in machine learning Ease of Use: Python’s syntax is simple and readable, making it accessible for both beginners and experienced developers. Extensive Libraries: Libraries like TensorFlow, Keras, scikit-learn, and PyTorch provide robust tools for machine learning tasks, from preprocessing to model deployment. Community Support: Python has a large, active community that contributes to a wealth of resources, tutorials, and support for troubleshooting. Integration: Python integrates well with other languages and technologies, facilitating data analysis, web development, and machine learning workflows. Flexibility: Python’s flexibility allows for the easy combination of different machine learning and data processing techniques. Benefits Of Using Python For Data Science Python libraries for machine learning has emerged as a go-to language for data science, offering a multitude of benefits that cater to the needs of professionals and learners alike. Simplicity and Readability One of the key advantages of python libraries for machine learning in data science is its simplicity. The language is designed with readability in mind, resembling the English language closely. This characteristic makes it an excellent choice for beginners, ensuring that even someone at a 6th-grade level can grasp the basics swiftly. Extensive Libraries Python boasts an extensive collection of ML libraries that significantly expedite the data science workflow. Libraries such as NumPy for numerical operations, Pandas for data manipulation, and Matplotlib for data visualization provide ready-to-use functions, reducing the need for coding from scratch. This streamlines the entire data analysis process, making it more efficient. Versatility Python’s versatility is another standout feature. It can seamlessly integrate with other languages and technologies, allowing data scientists to leverage existing systems effortlessly. Whether it’s connecting to databases, working with web APIs, or incorporating machine learning models, ML libraries python adaptability enhances its utility in various data science applications. Community Support The robust machine learning tools python community contributes significantly to its appeal in data science. With a vast and active user base, developers and data scientists can easily find support, resources, and solutions to challenges they encounter. This collaborative environment fosters learning and growth, making ML libraries python an excellent choice for those entering the field. Data Visualization Effective communication of insights is crucial in data science, and Python excels in this aspect. ML libraries like Matplotlib, Seaborn, and Plotly enable users to create visually compelling graphs and charts. This not only aids in understanding complex data but also facilitates conveying findings to diverse audiences, making machine learning with python a powerful tool for data storytelling. Scalability As data science projects evolve, scalability becomes paramount. Python’s scalability is evident in its ability to handle both small-scale data analysis tasks and large-scale, enterprise-level projects. This adaptability ensures that Python remains a reliable choice as data science requirements grow and become more complex. Ease of Integration with Big Data Technologies In the era of big data, Python’s compatibility with major big data technologies, such as Apache Hadoop and Spark, is a significant advantage. Data scientists can seamlessly integrate python libraries into their big data workflows, allowing them to analyze and derive insights from massive datasets efficiently. Benefits of Learning Python for Non-Programmers Learning machine learning with python holds numerous benefits for non-programmers, offering a gateway into the world of coding without overwhelming complexities. Whether you’re a student, professional, or hobbyist, machine learning modules user-friendly nature and versatility make it an ideal starting point for those new to programming. Ease of Learning Python’s syntax is designed to be clear and readable, resembling plain English. For non-programmers, this means a gentler learning curve. The simplicity of Python allows beginners to focus on understanding fundamental programming concepts without getting bogged down in convoluted syntax. Versatility and Applicability Python’s versatility extends across various domains, making it a valuable asset for non-programmers. From web development and data analysis to artificial intelligence and automation, Python finds applications in diverse fields. This adaptability ensures that learners can explore different areas of interest and tailor their programming journey according to their preferences. Abundance of Resources A vast and supportive community surrounds Python, providing an abundance of resources for learners. Numerous online tutorials, forums, and documentation make it easy for non-programmers to seek guidance and find solutions to challenges they may encounter. The wealth of resources fosters a collaborative learning environment, enhancing the overall learning experience. Community and Collaboration Python’s popularity has led to the formation of a vibrant and welcoming community. For non-programmers, this means access to a network of experienced developers willing to share knowledge and assist with problem-solving. Engaging with this community not only aids learning but also introduces individuals to the collaborative nature of programming. Extensive Library Support Python boasts an extensive collection of machine learning libraries and frameworks, simplifying complex tasks for non-programmers. These pre-built modules enable users to leverage powerful functionalities without delving into intricate code. This accessibility allows beginners to accomplish tasks efficiently, boosting confidence and motivation. Applicability in Data Science and Analysis For those interested in data science, Python’s popularity in this domain is a major advantage. Its libraries, such as NumPy and Pandas, provide robust tools for data manipulation and analysis. Non-programmers can easily grasp these tools, opening doors to opportunities in the rapidly growing field of data science. Automation and Productivity Learning Python introduces non-programmers to the world of automation. The language’s simplicity facilitates the creation of scripts to automate repetitive tasks, enhancing efficiency and productivity. This practical aspect is especially appealing to individuals seeking ways to streamline their workflows in various professional or personal settings. Career Opportunities Acquiring Python skills enhances non-programmers’ employability across industries. Many organizations value Python proficiency due to its widespread use and versatility. Learning Python provides individuals with a valuable skill set, making them competitive candidates in job markets where programming knowledge is increasingly in demand. How To Choose The Right Python Libraries For Your Needs? Choosing the right machine learning libraries for your needs is a crucial step in developing efficient and effective programs. Python’s extensive library ecosystem can be overwhelming, but a strategic approach ensures you select the tools that align with your specific requirements. Identify Your Project Requirements Begin by clearly defining your project’s objectives and requirements. Understanding the problem you aim to solve or the tasks you need to accomplish will guide your library selection. For instance, if you’re working on a machine learning project, libraries like TensorFlow or Scikit-learn might be relevant. Research and Understand Options Conduct thorough research on available libraries within the domain of your project. Explore documentation, user reviews, and community support to gauge the effectiveness and ease of use. This step ensures that you make informed decisions based on the library’s features and capabilities. Consider Library Compatibility Check the compatibility of the libraries with your Python version and other dependencies. Compatibility issues can hinder your project’s progress and lead to unnecessary complications. Choose libraries used in machine learning that seamlessly integrate with your existing technology stack to avoid roadblocks during implementation. Evaluate Performance Assess the performance of potential libraries used in machine learning by considering factors such as execution speed and resource utilization. Depending on your project’s nature, you may prioritize speed, efficiency, or memory usage. Understanding these aspects helps in selecting a library that aligns with your performance expectations. Community Support and Documentation Opt for deep learning with python with active communities and comprehensive documentation. A vibrant community ensures ongoing development, support, and troubleshooting resources. Well-documented libraries make it easier for you to understand and utilize the functionalities, reducing the learning curve. Scalability and Maintenance Consider the scalability of the deep learning with python in the long run. Choose tools that can accommodate future expansion or modifications to your project. Additionally, evaluate the maintenance aspect – libraries with regular updates and a history of addressing issues promptly are preferable for sustained development. Test the Libraries Before making a final decision, conduct small-scale tests with the shortlisted libraries. This hands-on approach allows you to experience the ease of use, functionality, and performance firsthand. Testing also reveals potential challenges or advantages that may not be apparent through documentation alone. Seek Expert Advice If you encounter difficulty in choosing between libraries, seek advice from experienced developers or experts in the field. Their insights can provide valuable perspectives and help you make an informed decision based on practical considerations. Future Of Python For Data Science Versatility and Accessibility Python’s versatility is a cornerstone of its enduring popularity. It serves as a multipurpose language, making it well-suited for a wide range of applications, including data science. Its syntax, resembling plain English, enhances accessibility, making it an ideal choice for both beginners and seasoned professionals. Rich Ecosystem of Libraries The extensive collection of libraries and frameworks in Python, such as NumPy, TensorFlow python, Pandas, and Scikit-Learn, forms a robust foundation for data science tasks. These libraries simplify complex operations, accelerate development, and contribute significantly to the language’s prominence in the data science community. Machine Learning Dominance Python’s dominance in the field of machine learning is a key driver for its future in data science. With libraries like TensorFlow and PyTorch, Python facilitates the development and deployment of machine learning models. Its adaptability to the evolving landscape of artificial intelligence ensures that Python will remain at the forefront of cutting-edge advancements. Community Support and Collaboration The thriving Python community is a testament to the language’s enduring success. The open-source nature of Python encourages collaborative development, leading to continuous improvements and innovations. This strong community support ensures that Python remains relevant and well-maintained, reinforcing its position in data science. Integration with Big Data Technologies As organizations grapple with vast amounts of data, Python seamlessly integrates with big data technologies such as Apache Spark and Hadoop. This adaptability positions Python as a go-to language for handling and analyzing large datasets, a crucial aspect of contemporary data science. Growing Job Market Demand The increasing demand for data science professionals translates into a burgeoning job market for Python experts. The language’s prevalence in data science roles across various industries, from healthcare to finance, underscores its indispensability. As this demand continues to rise, proficiency in Python will likely become a valuable skillset. Continuous Development and Updates Python’s commitment to regular updates and improvements ensures that it stays relevant in the face of evolving technological landscapes. The language’s adaptability to incorporate the latest features and address emerging challenges solidifies its place in the future of data science. Conclusion Python is the go-to language when it comes to data science and machine learning and there are multiple reasons to choose python for data science.  You can check out IIT Delhi’s Advanced Certificate Programme in Machine Learning in association with upGrad. IIT Delhi is one of the most prestigious institutions in India. With more the 500+ In-house faculty members which are the best in the subject matters. Python has an active community that most developers create libraries for their own purposes and later release it to the public for their benefit. Here are some of the common machine learning libraries used by Python developers. If you want to update your data science skills, check out IIIT-B’s Executive PG Programme in Data Science program. 

by upGrad

19 May 2024

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Wondering what is the range of DevOps Salary in India? In the last few years, DevOps has evolved from being just a “buzzword” to a mainstream practice in the IT world. According to Statista, as more and more organizations are adopting DevOps, there has been a 17% increase in 2018 from only 10% in 2017.  Source  Furthermore, the 2019 State of DevOps Report by Puppet Labs shows a positive trend in the global adoption of DevOps. Because of this reason, companies are not shying away from offering increased DevOps salary in India. Check out our free courses related to software development. Source Thus, if you have the required skillset and are ready to keep yourself updated, your career as a DevOps Engineer is expected to keep growing onwards and upwards. This line stands true especially when we consider that a DevOps salary in India is directly or indirectly dependent on how upskilled and updated they are. Explore Our Software Development Free Courses Fundamentals of Cloud Computing JavaScript Basics from the scratch Data Structures and Algorithms Blockchain Technology React for Beginners Core Java Basics Java Node.js for Beginners Advanced JavaScript Check out our best devops courses at upGrad Our Learners also read: Devops career path! This, in turn, has spurred the demand for skilled DevOps professionals, who are among the highest-paid IT professionals today. Tech giants like Oracle, Barclays, Accenture, Tech Mahindra, TCS, IBM, Wipro, Facebook, to name a few, are always seeking professionals with DevOps skills. Even e-commerce companies like Target, Amazon, eBay, etc. are readily adopting DevOps, thereby creating plenty of employment opportunities for DevOps professionals. The top roles in DevOps include DevOps Architect, DevOps Engineer, DevOps manager, Security Engineer, Automation Engineer, and Release manager. The demand for these engineers are always high. The list is endless. That’s the primary reason DevOps salary in India is quite high. The ever-increasing demand. Check out our Advanced Certification in DevOps We are sure, this must-have sparked a will to become a DevOps Engineer within you! Let’s take a look at who exactly is a DevOps Engineer and what is a typical DevOps salary in India? One-Of-Its-Kind Program That Creates Skilled Software Developers. Apply Now! Get Software Engineering degrees from the World’s top Universities. Earn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. What is DevOps? DevOps is nothing but a set of cultural practices, philosophies, and tools that help n organization to deliver applications and services faster than usual and improve and evolve their products at a much brisker pace than software development organizations that are still stuck with traditional infrastructure management processes. This ability to work at speed allows organizations to develop a much-needed competitive edge and at the same time, serve their customers in a better way. It is a term that has emerged out of the coming together of two related concepts. One of these concepts is agile operations or agile infrastructure. Agile operation is a concept that involves the application of Lean and Agile methodologies to operations. The second concept is a much broader one and involves a thorough understanding of how collaboration between development and operations teams through the software development lifecycle brings value. Because of the demand, DevOps salary in India is one of the highest. Explore our Popular Software Engineering Courses Master of Science in Computer Science from LJMU & IIITB Caltech CTME Cybersecurity Certificate Program Full Stack Development Bootcamp PG Program in Blockchain Executive PG Program in Full Stack Development View All our Courses Below Software Engineering Courses upGrad’s Exclusive Software and Tech Webinar for you – SAAS Business – What is So Different? document.createElement('video'); https://cdn.upgrad.com/blog/mausmi-ambastha.mp4   What does a DevOps Engineer do? DevOps Engineers work in close collaboration with Software Developers, System Operators (SysOps), and other production IT members to manage and supervise code releases. They must be well-versed in IT infrastructure management that is integral for supporting the software code in dedicated, multi-tenant, or hybrid cloud environments. Our learners also read: Java free online courses! In a DevOps model, the development and operations teams do not function separately as ‘siloed’ units but merge together. Also, this approach to software development demands frequent and incremental changes. Hence, DevOps Engineers have to perform a wide range of functions across the entire application lifecycle – from development and test to deployment and operations. This calls for a versatile skill set that is not limited to a particular function or role. Check out our Advanced Certification in Blockchain To successfully implement the DevOps approach, DevOps Engineers must be well-versed in the best practices of DevOps methodology, which include: Continuous Integration – This practice requires developers to merge the alterations in their code into a central repository, after which it runs the automated builds and tests. Continuous Delivery – In this practice, the code changes are built, tested, and prepared automatically for the production release. Continuous deployment (CD) –This practice is about automatically submitting the changes done by a developer from the repository to the production process. It, therefore, saves valuable time because the operations team need not do it themselves. Infrastructure as Code – This practice encourages the provision and management of the infrastructure using specific code and software development techniques (version control, continuous integration, etc.). Monitoring and Logging – Monitoring and logging are essential to check and measure the metrics of applications and infrastructure and see how their performance affects the user experience of a product/service. With suitable monitoring, you can rapidly troubleshoot problems with the help of root cause analysis that identifies where a problem started. The AWS devops engineer salary because these engineers are skilled at monitoring and logging processes. Monitoring helps them identify how various systems influence each other –when they operate sequentially and simultaneously. A DevOps engineer’s job is nearly impossible without an exhaustive monitoring solution. Conversely, if a DevOps engineer can monitor all elements of your stack, the time-consuming and major issues can be quickly resolved. So, the ability to develop a quick solution suggests a decent AWS devops engineer salary. Communication and Collaboration – DevOps encourages increased communication and collaboration within organizations. Microservices Architecture – It is a design approach used to develop a single application as a component of small services. So, there are opportunities galore for DevOps developers, and the indispensable nature of their jobs ensures that DevOps salary in India is quite elevated. Container orchestration -DevOps engineers use container orchestration to ensure processes execute automatically and more efficiently. It also helps them to ascertain that designing rules dictate the conditions under which containers are shut down or spun up. Commonly, containerization is used to stabilize the use of resources as per the existing workload.  You can earn an admirable AWS devops engineer salary in India after learning how to build containers, Java, Go, Node.js, and Python 3. Now, we move on to the main functions and responsibilities of a DevOps Engineer. In-Demand Software Development Skills JavaScript Courses Core Java Courses Data Structures Courses Node.js Courses SQL Courses Full stack development Courses NFT Courses DevOps Courses Big Data Courses React.js Courses Cyber Security Courses Cloud Computing Courses Database Design Courses Python Courses Cryptocurrency Courses Responsibilities of DevOps Developer To make your career to grow as a DevOps developer and earn the highest possible DevOps salary in India, you need to have been familiar with these responsibilities: 1.Project Planning DevOps Engineers are an integral part of the project planning operation. Their skills in software development and system options, and business expertise (the risk, impact, and costs vs. benefits) allows them to foresee the project needs and resources. 2. Product Development DevOps Engineers are responsible for developing, building, and managing IT solutions. To meet this end, they have to install and configure solutions, implement reusable components, translate technical requirements, perform script maintenance and updates, assist operations teams at all phases of data testing, develop interface stubs and simulators, to name a few. 3. Product Deployment DevOps Engineers design and develop automated deployment arrangements by leveraging configuration management technology. This allows them to deploy new modules/upgrades and fixes in the production environment itself. 4. Performance Management Apart from evaluating existing applications and platforms, DevOps Engineers also offer recommendations for enhancing the performance. 5. Maintenance and Troubleshooting Maintenance and troubleshooting are two routine tasks of DevOps Engineers. Using strategy-building techniques, they delineate the requirements and procedures for implementing regular maintenance. 6. Security Integration DevOps developers bear the crucial responsibility of integrating security practices flawlessly into every stage of software development and hold high devops salary in India. This pivotal role includes incorporating stringent security measures from code inception to deployment phase, thereby empowering developers to identify and resolve vulnerabilities in early developmental phases – a process that ensures alignment with rigorous end-product security standards. 7. Capacity Planning and Scalability DevOps Developers analyze system performance and ensure that the infrastructure can scale to meet increasing demands, with decent devops engineering salary in India. Through diligent capacity planning, they anticipate resource requirements proactively. With the given devops engineer salary, they fine-tune the system for optimal efficiency during peak periods, a process which underlines their pivotal role in crafting systems – ones capable of expanding effortlessly in response to evolving user demands. This approach accentuates scalability’s crucial aspect and managing heightened workloads becomes more manageable as a result, in such devops salary, especially, devops salary India. 8. Disaster Recovery Planning DevOps Developers significantly contribute to creating and testing disaster recovery plans. These strategic blueprints guarantee the swift restoration of systems and data in unforeseen outages or catastrophes. Through consistent plan development coupled with rigorous testing, DevOps Developers play a vital role in minimizing downtime for organizations. Moreover, they secure continuity of critical business operations, an invaluable asset for any company,  with such devops fresher salary in India. 9. Cost Optimization Optimizing resource utilization to minimize infrastructure costs falls under the responsibility of DevOps Developers,  especially in such devops fresher salary. They must monitor and analyze resource consumption, identify areas of inefficiency, and implement strategies to reduce operational expenses. The organization’s financial sustainability benefits when DevOps Developers adopt cost-effective solutions, mostly with bearing average salary of devops engineer in India, or aws devops salary in India. 10. Automation of Business Processes DevOps Developers not only automate the software development lifecycle, but they also extend this automation to business processes. Their efforts involve automating repetitive tasks and workflows as well as streamlining overall operations through reducing manual interventions thus minimizing human error. By enhancing efficiency with automation, they accelerate time-to-market and guarantee consistency in the delivery process. 11. Knowledge Sharing and Training Fostering a culture of continuous learning and knowledge sharing within the organization is the vital role DevOps Developers play,  including cloud devops engineer salary, and senior devops engineer salary. Their responsibilities include conducting training sessions, creating documentation notably for best practices in DevOps principles and tools, a task paramount to ensuring team-wide proficiency. By facilitating this transfer of expertise, teams remain aligned, enhancing collaboration and hastening their adoption of new technologies thus reaping significant benefits from shared knowledge. DevOps Developers deeply involve themselves in project planning, development, and deployment among other well-established responsibilities. Their contributions also span critical areas of security integration, capacity planning, disaster recovery planning and cost optimization – all key elements for organizational success. Furthermore, automation of business processes and knowledge sharing not only drive innovation but foster efficiency and collaboration within the workplace. It’s a dual-purpose approach that distinguishes proficient DevOps developers from their peers, like aws devops  salary, and azure devops engineer salary. Read: Career in DevOps DevOps RoadMap Understanding the working of Cloud Service Platforms: Modern IT infrastructure often builds its foundation on cloud service platforms. A DevOps practitioner, further expanding into this domain, must explore specific cloud providers such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). With a comprehensive understanding of these platforms’ nuances, their services, deployment models and pricing structures, DevOps engineers can optimize infrastructure as they harness the full potential of solutions based in the clouds. Furthermore, it is crucial to master Infrastructure as Code (IaC) tools such as Terraform and CloudFormation. The codification of infrastructure through IaC promotes consistency and scalability. Therefore, proficiency in these tools becomes indispensable. Aligning with the DevOps ethos of automation and reproducibility involves learning how to design, provision, and manage infrastructure via code. One should learn the working of Cloud service platforms because many companies are using their infrastructure on the cloud. It is an essential skill which should be learned. Knowledge of Using Tool to Monitor and Collection of Important Feedback: Continuous improvement drives DevOps, with its core being effective monitoring. Although valuable tools such as Splunk and Nagios exist, a deeper understanding of system performance, resource utilization, and application behavior can emerge by delving into advanced solutions like Prometheus and Grafana. DevOps engineers, in their pursuit of proactive issue identification and resolution, must grasp the setup of meaningful alerts, dashboards, and logs. They should also integrate with incident response systems like PagerDuty or OpsGenie for instance to guarantee a swift reaction to potential disruptions. This is crucial. Further exploration into Application Performance Monitoring (APM) tools such as New Relic or Datadog is recommended. It grants them visibility into application-level performance. Implementation of changes as soon as possible after the collection of feedback is an essential skill for a DevOps Engineer. Knowledge of Monitoring tools such as Splunk, Nagios and many more are necessary for a DevOps Engineer to learn. Knowledge and Experience of Deployment of Application: In ensuring smooth and reliable application delivery, pivotal roles are played by deployment strategies. Docker and Puppet serve as essential tools. However, extending the knowledge to Kubernetes for container orchestration enhances the ability with a dash of efficiency to manage complex applications based on microservices effectively. Embracing practices such as Infrastructure as Code which defines and automates deployment pipelines using tools like Jenkins, GitLab CI, or CircleCI, we foster consistency and repeatability. Further automation through Continuous Deployment (CD) minimizes the release process’s manual interventions. A DevOps Engineer should know how to deploy in the server of production. Knowledge of Configuration and Deployment in the production environment by using tools such as Docker and Puppet is beneficial. Knowledge of Continuous Testing, Continuous Delivery, and Continuous Integration Adopting a holistic approach to testing and seamlessly integrating it into the development pipeline is the imperative of every DevOps engineer. In addition to automated unit tests, a baseline requirement, considering Behavior-Driven Development (BDD) frameworks such as Cucumber or Behave not only enhances collaboration between QA teams but also fosters an environment where developers are more aligned with quality assurance objectives. By implementing Continuous Integration (CI) using tools such as Jenkins or GitLab CI, we ensure regular integration, testing and validation of code changes. When coupled with Continuous Delivery (CD), this process automates the deployment of tested code into production-like environments thus fostering a culture that promotes frequent and incremental releases. DevOps need to know how things can be automated in the testing stage. The code should be less complicated so that it can run fine in both development and testing environments. Good Knowledge of Tool for Source Code Management and Build Tools: DevOps engineers should extend their understanding of version control systems beyond Git. They ought to delve into advanced Git workflows like Gitflow or GitHub Flow. Proficiency in managing branches effectively, resolving conflicts and preserving a clean commit history enhances the efficiency of development processes. Gradle and Maven, two standout build tools in their field, offer potent capabilities for dependency management and project automation. When we integrate these tools into the CI/CD pipeline, a procedure that emphasizes continuous integration and delivery of software updates, we secure an efficient, reproducible and scalable build process. A competent DevOps Engineer should know how to process the building of automation. One should know how to build the commit continuously. There are some automation servers that DevOps should know, such as the working of Jenkins. Skills of Source Code Management: Foundational proficiency in Git remains essential. However, a DevOps engineer must also delve into the advanced features of Git. This involves grasping concepts such as rebasing and cherry-picking, along with submodule management. These provide a more nuanced approach to codebase control. Furthermore, by exploring Git hooks, it’s possible to automate both pre- and post-commit tasks, consequently enhancing the overall development workflow. A deep understanding of GitLab or GitHub Actions for automating workflows is essential encompassing the critical processes of testing, building and deploying applications. By harnessing capabilities inherent within these platforms one can realize a development lifecycle that’s not only more integrated but also vastly automated. A DevOps Engineer should have proficiency in at least one source code management tool (version control system) such as Git. Average DevOps Salary in India The demand for DevOps is high but companies require individuals to have the correct skill sets. Additionally, the better the experience, the higher is the salary. The average devops salary in India, according to Payscale, is Rs 674,202 per year, inclusive of bonuses and profit-sharing. Source City Average Annual Salary Bangalore ₹8.4 Lakhs Mumbai ₹8.3 Lakhs Hyderabad ₹8.2 Lakhs Pune ₹8.5 Lakhs Kolkata ₹7.6 Lakhs Chennai ₹8.3 Lakhs Source Factors Affecting DevOps Salary in India The four main factors affecting the DevOps Salary in India are: Company – The company that you work for will have a direct impact on the salary you get. Experience – The more experience you have, the better is ability to understand the roadblocks and provide quick solutions for bugs. A combination of experience and company will get salaries and positions that help create a mark. Location – In the coming years, location is all set to play a smaller role in the salary you can expect. But, even then, location will continue to have an impact on the salary you can ask for and get from a prospective employer. Skill – The important skills you have, the better is the ability to understand. Location is all set to play a vital role in deciding the DevOps engineer salary in India. DevOps Salary in India: Based On Company It is an accepted fact, the bigger the brand or company, the higher is the salary an individual can expect. Let us look at some of the highest pay packages – Tata Consultancy Services Limited offers about Rs. 6,27,000 per annum as salary. It is followed by Accenture Technology Solutions at Rs 5,63,000. DevOps engineer salary Chennai and other cities depend on the employer. Source Companies Average Annual Salary Forbes Global 2000 ₹8.6 Lakhs Public ₹8.3 Lakhs Fortune India 500 ₹7.8 Lakhs Conglomerate ₹8.5 Lakhs Startup ₹8 Lakhs MNC ₹11.4 Lakhs Source DevOps Salary in India: Based on Experience The more experience you have the higher your pay package will be. So, if you are a beginner and have only recently entered the industry, you will have to moderate your hopes accordingly. So, let us break down the DevOps engineer salary in India, depending on how many years of experience you have in your bag – Let’s see how a DevOps engineer salary in India varies based on experience. Source Entry-Level Engineer Salary in India The average entry-level DevOps salary in India is ₹366,337. Source Mid-Level DevOps Salary in India The average mid-level DevOps salary in India is ₹1,142,206. Source Experienced DevOps Salary in India The average experienced DevOps salary in India is ₹1,632,155. Source Let’s see how the DevOps engineer in India increases with experience: Source Years Experience Average Annual Salary 2 Years ₹5.6 Lakhs 3 Years ₹6.6 Lakhs 4 Years ₹7.9 Lakhs 5 Years ₹9.7 Lakhs 6 Years ₹11.4 Lakhs Source DevOps Salary in India: Based on Location Though Covid-19 may reduce the impact of location on salaries in the future, currently, location plays a crucial factor in determining DevOps salary in India. The Silicon Valley of India, Gurgaon, Haryana offers the highest salaries, with DevOps engineers in the city earning approximately 20% more than their counterparts in other cities. The comparison is done against the national average. Chennai, Tamil Nadu the other city competing for the Silicon Valley title, offers salaries that are 9% less than the national average. So, you can expect admirable DevOps engineer salary Chennai and DevOps engineer salary Mumbai. Source City Average Annual Salary Bangalore ₹8.4 Lakhs Mumbai ₹8.3 Lakhs Hyderabad ₹8.2 Lakhs Pune ₹8.5 Lakhs Kolkata ₹7.6 Lakhs Chennai ₹8.3 Lakhs Source DevOps Salary in India: Based on Skills Let’s discuss how DevOps engineer salary in India increases with the skillset. As we mentioned earlier, you have to possess an impressive set of skills to acquire the best-paid jobs in the highly competitive market for DevOps engineers. Some skills get you a higher paycheque. So, try to invest in these skills. Development Operations(DevOps) – ₹694,145 Amazon Web Services(AWS) – ₹683,831 Linux – ₹671,250 Jenkins – ₹692,795 Python- ₹723,891 Source Development Operation and Amazon Web Services are sure to bring you more than the average DevOps engineer salary in India. In terms of popularity response too, these two skills ranked the highest. DevOps Salary in Other Countries DevOps engineer salary Mumbai and other Indian cities are admirable but let’s now look at the DevOps salary in other countries. DevOps salary in The US is $94,366. Source DevOps salary is The UK is £41,855. Source Most Demanding DevOps Skills 1. Linux Fundamentals And Scripting Gone are those days when companies worried about proprietary operating systems. We are now in the era of Linux. Most companies prefer hosting their applications on Linux. As such, skills in handling a Linux operating system are very crucial for a DevOps Engineer. So, a DevOps Engineer must be able to handle any scripting language and must be well-versed with at least one scripting language (preferably Python). So the inevitable DevOps skillset would be Linux and Linux based scripting. 2. Knowledge On Various DevOps Tools And Technologies DevOps practices are executed in various stages, and each stage has tools that can facilitate that stage. The main stages are Source Code Management Developers create and modify the software codes regular. Source code management software is used to store the code, merge new code to the old one, control the code versions, etc.  Configuration Management Configuration management is used to keep track of software and operating system configurations. It also helps to manage configurations across thousands of servers. It is done through a click of a button or the execution of a single command on the management server. Continuous Integration Continuous integration, abbreviated as CI, is the process of automating the code integrations from different developers into a single piece of software. Continuous Testing Continuous testing is the process of reducing feedback waiting time after code testings. The code is tested in the development environment itself using automation testing tools. Continuous Monitoring Continuous monitoring is used to monitor application performance, downtimes, error logs, etc. The main tools used are Nagios, Zabbix, Splunk, etc. Containerization Containerization is the process of virtualizing an operating system so that different containers running different applications can share the operating system and system resources. Containerization allows isolating processes from the other part of the software. Every container works as a virtual machine that runs a piece of the entire process. Many organizations evaluate the knowledge of containerization when they evaluate AWS devops salary. Since containers can be shut down and spun up very quickly, containerization makes it simpler and cost-effective to use various aspects of the software. A DevOps engineer must understand containerization because it influences how a product is developed, tailored, and tested. DevOps engineers skilled in these aspects can earn admirable AWS devops salary. 3. Continuous Integration And Continuous Delivery Continuous Integration And Continuous Delivery or abbreviated as CI/CD is the essence of DevOps. It is the practice of continuously integrating all the code from different developers, continuously testing them, and deploying the successful code to production. 4. Infrastructure As Code Previously provisioning IT infrastructure was a long, tedious, and manual process. With the birth of cloud computing and containerization technologies, the infrastructure needed by developers can be provisioned through an automated script. 5. Key concepts of DevOps  DevOps unlike what people think, is neither a technology nor a tool. It’s a methodology that doesn’t have a strict framework. So companies can adopt the methodology by tailoring the framework as per their standards. 6. Soft skills Soft skills play a great role in the IT industry with the adoption of DevOps methodology. Most companies prefer an Agile way of working using DevOps methodologies so that teams work in high velocity and produce deliverable faster to meet client expectations.  How does a DevOps Engineer enhance the DevOps culture? People consider DevOps more inclined towards a cultural shift rather than an innovative development method. DevOps engineers enhance a culture of collaboration, communication, and shared responsibility between all parties for the whole development lifecycle. One of the greatest challenges a DevOps engineer faces is letting all stakeholders work together. The stakeholders include front-end developers, back-end developers, UI/UX developers, product testers, IT operations admins, security admins, executives, and customer service Reps who deal with end-users. All these stakeholders are equally significant in the DevOps culture. Their respective visions share the same value.  The AWS devops engineer salary in India is increasing because these engineers are expected to bring a cultural shift. This shift may need developers and executives to improve their listening skills. A DevOps Engineer may need to guide them through the cultural shift process. 1. Promoting Collaboration The DevOps salary in India hinges on the ability to merge the operations and development teams. Essential is the encouragement of open communication and collaboration, traditionally limited in these departments. This undertaking, organizing cross-functional team meetings, fostering an environment where knowledge is shared freely, requires not just technical proficiency but also promoting empathy within developers,testers, and personnel from operations. A DevOps Engineer dismantles communication barriers, thereby fostering a work environment characterized by collaboration and cohesiveness. 2. Emphasizing Continuous Learning DevOps, a field perpetually in evolution, witnesses regular emergence of new tools and practices. A culture rooted in continuous learning, an environment the DevOps Engineer must foster within their team, requires not only organization of training sessions but also sharing industry trends along with best practices. Most importantly, it needs nurturing an experimental mindset that accepts failures as opportunities for growth and learning. A DevOps Engineer fosters an environment of adaptability and innovation by actively staying current with the latest developments, sharing knowledge, and promoting a culture that values continuous learning. 3. Establishing a blame-free Culture The software development process inherently incorporates failure. In emphasizing a blame-free approach to failures, a DevOps Engineer contributes positively to the culture. Rather than attributing issues with blame, we should focus on identifying root causes, learning from mistakes. A proactive attitude towards problem-solving receives encouragement from this culture shift. Moreover, it nurtures an environment in which team members feel secure to take risks and innovate. 4. Implementing DevOps Metrics Subjective feelings of collaboration do not solely define DevOps. We can quantify and measure it. A DevOps Engineer has the ability to introduce key performance indicators (KPIs) that gauge several aspects, including the development pipeline’s efficiency, deployment frequency, lead time and even mean time for recovery. This data-driven approach enhances transparency and accountability, contributing to a culture of continuous improvement. 5. Encouraging Cross-Functional Skills To obtain a good DevOps salary in India a DevOps Engineer ought to champion cross-functional skill development within the team. This entails fostering an environment where developers comprehend operations and vice versa. Through cultivating a culture that liberates team members from confinement in their specific roles, thereby promoting holistic understanding of the entire software delivery process, a versatile and adaptable team emerges. How to Become a DevOps Engineer? You must obtain the experience and knowledge required to work with different technologies and teams if you want to become a DevOps engineer. It is crucial to learn the skills, implement them, and develop a portfolio that would impress potential employers to offer a praiseworthy DevOps engineer salary. It is better to work with different coding languages to understand how they are used to create solutions. Expanding your tech stack makes it simpler to troubleshoot issues and explain to stakeholders the opportunities and limitations. Another crucial aspect when it comes to earning a decent DevOps engineer salary is to become comfortable working with people from various backgrounds who specialize in different disciplines. Pursuing a relevant course can help in these cases. As you learn relevant skills, interact with various types of learners and tutors, and amass your portfolio, you will embark on your DevOps career with a nice Azure DevOps salary in India. What does it take to be a DevOps Engineer? At its core, the concept of DevOps seeks to combine and integrate the development and operations sides of software development into one continuous process. It encompasses the features of agile development, continuous integration, and continuous delivery, while also focusing on encouraging collaboration across the various IT departments (development, operations, support, and management teams). A DevOps Engineer is an IT professional with expertise in DevOps. These professionals have an extensive understanding of the software development life cycle (SLDC) and are adept in using a host of engineering tools and processes to solve complex operations challenges. Typically, DevOps Engineers have to juggle with different tasks, including coding, integrating, and testing – all aimed to enhance collaboration between teams and boost the development process.  As for the educational requirements, a DevOps Engineer must at least have a bachelor’s degree in Computer Science/Information Technology or any other related discipline. Apart from this, a strong foundational knowledge of data center migrations is beneficial. Other skills that a DevOps Engineer should possess are – SQL, Linux, Unix, MySQL, Python, Java, MongoDB, Puppet, Maven, Crucible, Jenkins, Software Configuration Management, and Cloud services (AWS/ Rackspace, Docker, OpenShift, etc.).  While the job role of a DevOps Engineer usually demands around 2-5 years of work experience in DevOps platforms, senior-level positions like that of a DevOps Architect/Manager, require at least 10-12 years of DevOps experience.  Some of the most in-demand skills of a DevOps Engineer are: Excellent technical understanding of cloud infrastructure services like Azure, AWS, etc. In-depth knowledge and working experience in compute virtualization, automation, and DevOps methodologies. Proficiency in environment management (Linux/Unix, Windows, Shell Scripting, Ansible, Chef, Puppet, etc.) Proficiency in coding and experience in Software-Defined Data Centers maintenance. Proficiency in writing and maintaining deployment scripts. Expertise in managing nodes and diagnosing application services and server/ network issues. DevOps Roles and Responsibilities  DevOps philosophy is fast evolving and new designations, roles, and responsibilities and emerging. An interesting fact is that though companies list these roles separately, there is a lot of overlap on the responsibilities, duties, and skill requirements. As of today, most companies have the below list of job titles for DevOps engineers DevOps Architect A DevOps architect is responsible for analyzing and executing DevOps practices within the organization or a team. He architects the overall DevOps environment bringing in all efficient DevOps methodologies as per industry standards. He brings in the right tools for automation of the processes. Automation Architect The Automation Architect is a crucial role in modern DevOps. A large number of DevOps depend on automated processes and workflows that streamline teams and reduce the need for intervention. So, the Automation Architect is one of the critical DevOps roles that can offer a great Azure devops salary in India. Candidates skilled with the Automation Architect position possess a profound familiarity with DevOps platforms as well as integrations. They can quickly troubleshoot and solve problems. Release Manager In a DevOps environment, a release manager is responsible for planning, scheduling, monitoring, and controlling the software development and deployment process. He develops the development team and the operations team to be in sync, enabling frequent but short feedback loops. From a DevOps perspective, the Release Manager is a significant management and oversight position that demands a profound level of practical development knowledge. Leadership is the key priority of this role. They are not only tasked with coordinating multiple releases and comprehending CI/CD but also need to map development pipeline strategies and coordinate those amongst teams. Security Engineer In the DevOps, world security is popularly known as DevSecOps. The responsibilities include using different tools like log management and configuration management to ensure security throughout. DevOps emphasizes on a continuous security philosophy. Security is a crucial aspect of the development process in DevOps. Security must be parched into the product from the ground to make sure it is harder to crack. This can be achieved by a security engineer who can closely work with the software developers. The DevOps engineer salary in India for 2 years experience can be high if they are skilled at ensuring system security. Security Engineers are important not only for a product’s success but also to guarantee safe operation.  These DevOps engineers must be fluent with contemporary security standards, continuing attack vectors, and user behaviours that commonly bypass security and create holes. Automation Engineer In the DevOps world, an automation engineer is responsible for developing and maintaining the CI/CD process for all the applications and their builds using tools like Maven, Jenkins, Git, Gerrit, Gradle, etc. He would be automating the configuration management across the infrastructure and platforms using configuration management tools like Ansible, Chef, Puppet, SaltStack, Fabric, etc. Software Tester A test engineer in the DevOps culture has to align their test design, test cases, and test automation with the DevOps framework being used. A software tester verifies that the code changes work as intended and also makes sure that the changes do not break the software product as a whole. Integration Specialist An integration specialist works with the infrastructure operations teams and software development teams to create the integration and continuity of the code. He creates a holistic view of the working environments. He supports engineering and testing teams to meet infrastructure needs. Read our Popular Articles related to Software Development Why Learn to Code? How Learn to Code? How to Install Specific Version of NPM Package? Types of Inheritance in C++ What Should You Know? DevOps or Platform Engineer: If the organization is adopting a DevOps approach, it usually appoints a Platform Engineer to support the platform’s infrastructure. This infrastructure includes different managed services and in-house development. A DevOps or Platform engineer can get a decent DevOps engineer salary in India for 2 years experience if they can effectively support the platform’s infrastructure.  Site Reliability Engineer: Also known as Reliability Engineer, a Site Reliability Engineer is accountable for guaranteeing the quality of orchestration and integration of tools required to support daily operations. When people think about DevOps initially, this is the ideal role that strikes minds. They skillfully patch the existing infrastructure with data storage infrastructures and cloud solutions. This job role is significant in all DevOps organizations because the inability to guarantee sound integration can lead to costly outages. Data Analyst: DevOps Data Analysts examine and derive data to fulfil development goals. They are an important member of the development team because they use user data and existing data to critically think about patterns that influence user experience and other design issues. Some of their responsibilities overlap with QA Analysts and UX designers. Product Manager: It is the only job position in this list that is chiefly an operations position. Being operations team members, the product managers are tasked with collaborating with the dev team to ascertain that the product’s requirements are fulfilled to a high-quality standard. The ability to ensure product requirements are met can increase the chances of a decent DevOps engineer salary in India for 2 years experience as DevOps engineer. Top Companies Hiring DevOps Engineers in India Amazon With its extensive cloud services through Amazon Web Services (AWS), Amazon has consistently needed DevOps professionals to manage and optimize their cloud infrastructure. Google Businesses widely use Google Cloud Platform (GCP), and Google frequently looks for DevOps experts to enhance their cloud services and infrastructure. Microsoft Microsoft Azure is a leading cloud computing platform, and Microsoft often recruits DevOps engineers to work on Azure’s deployment, monitoring, and management solutions. Infosys As one of India’s largest IT services companies, Infosys frequently hires DevOps engineers to support its clients’ digital transformation initiatives, implementing DevOps best practices. Tata Consultancy Services (TCS) TCS is another major IT service player, actively seeking DevOps professionals to assist their clients in streamlining development and operations processes. Wipro Known for its IT services and consulting, focusing on digital transformation. DevOps engineers play a crucial role in their projects related to cloud computing and software development. Accenture Accenture, a global consulting and professional services company, often hires DevOps engineers to help clients accelerate their digital transformation journey through efficient software development and IT operations. IBM This company has a significant presence in India and continues to hire DevOps engineers to work on varied projects like, cloud computing, artificial intelligence, and data analytics. Paytm One of the leading multination company in India, Paytm invests in technology and frequently recruits DevOps experts to maintain their high-traffic platforms and ensure seamless operations. How to Obtain a Competitive DevOps Engineer Salary? Here are several key steps to help you obtain a competitive salary in the DevOps field: Master Core Skills Develop expertise in key DevOps tools and technologies like Docker, Kubernetes, Jenkins, Ansible, Git, and scripting languages like Python. Understanding the entire software development lifecycle is crucial. Continuous Learning DevOps is a rapidly evolving field. Stay updated with the latest trends, tools, and best practices. Regularly upskill through online courses, certifications, workshops, and attending industry conferences. Gain Practical Experience:  Apply your skills in real-world projects through internships, freelance work, or personal projects. Practical experience enhances your problem-solving abilities and makes you more valuable to employers. Collaboration and Communication DevOps is not just about technical skills; it also involves effective collaboration and communication between development and operations teams. Develop strong interpersonal skills and the ability to work well in a team. Certifications Consider earning certifications such as AWS Certified DevOps Engineer, Kubernetes Administrator, or Docker Certified Associate. Certifications validate your skills and can significantly boost your earning potential. Version Control and Collaboration Proficiency in version control systems (like Git) and collaboration platforms (like GitHub) is essential. Employers look for candidates who can efficiently manage code repositories and collaborate effectively with team members. Problem-Solving and Automation DevOps engineers should excel in problem-solving and be adept at automating repetitive tasks. Automating manual processes increases efficiency and productivity, making you invaluable to employers. Soft Skills Develop soft skills such as leadership, adaptability, and resilience. DevOps engineers often work in fast-paced environments where these skills are highly valued. Conclusion The opportunities for DevOps Developers are currently at their prime in India. We hope you liked our article on DevOps Developer’s salary in India. These numbers above are not set in stone. The real influencer of your salary is the skills you have,  the mastery you have attained over them, and how quickly you grow and make the company grow as well. By the end of this article, we hope we have given you the answers to your queries like Devops engineer salary for freshers, DevOps engineer salary in India for 2 years experience, DevOps engineer salary in India per month, DevOps engineer salary in India for freshers, DevOps engineer salary per month, DevOps engineer salary in India for 3 years experience etc. If you’re interested to learn more about DevOps, full-stack software development, check out upGrad & IIIT-B’s PG Diploma in Full-stack Software Development which is designed for working professionals and offers 500+ hours of rigorous training, 9+ projects, and assignments, IIIT-B Alumni status, practical hands-on capstone projects & job assistance with top firms.

by upGrad

19 May 2024