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AWS Solution Architect Salary in US

Updated on 30 November, 2022

5.36K+ views
7 min read
AWS Solution Architect Salary in US

The onset of cloud computing has revolutionized the tech market to seek out better ways to serve customers with high-end services. It’s not just an option but a necessity now for thousands of businesses to establish their lead processes on the web. Services like storage, security, networking, and remote computing are meant to be accessible. Therefore, the need to find the right candidate to handle such complex roles is growing too. 

An AWS Solution Architect is the one who monitors this domain with tech expertise and adds fluency in cloud computing services such as AWS. AWS Solution Architect serves as an exceptionally lucrative career with growing industry demand that will grow in the coming years. According to the Cloud Security Alliance, around 41.5% of the total cloud computing market is held by AWS. However, the market is failing to fulfill the need for AWS-certified professionals. 

Let’s dive in to know more about career opportunities as an AWS Solution Architect and what it offers to candidates looking to leverage a successful career in the IT industry.

What is AWS?

AWS or Amazon Web Services is a broadly adopted cloud computing platform extended by Amazon. The service is extended on a pay-as-you-go format, allowing users to access the convenience of remote computing, data storage, and content delivery services. It follows an easy, one of its kind pay-to-use model which is easily accessible by individuals for personal endeavors, companies to set up their diverse processes without hardware investments, and governments to help them keep up with the IT modernization. 

Amazon Web Services offers certificate courses in diverse IT domains relevant to cloud computing. It allows candidates to equip themselves with technical cloud skills to help businesses set up their company models over the web, from storage to security essentials. The platform provides everything, and AWS-certified candidates offer businesses insights into leveraging these features for growth. The certification can be obtained following a three to six months long course concluded by an exam to gain certification.

Who is an AWS Solution Architect?

An AWS Solution Architect is an IT professional with AWS certification. They are technical experts who form the base of any company for cloud computing. AWS Solutions Architect plans out the architecture of a brand’s cloud resources and aligns it accurately with their cloud strategy towards smooth implementation. Solution Architects usually analyze the business requirements of any brand and help them acquire software or infrastructure aid for improvement. Similarly, AWS certified Solution Architects follow the same pattern but prepare companies for web presence and cloud computing strategies. AWS Solutions Architect is one of the most sought-after careers worldwide.

Career as an AWS Solutions Architect in the US

The US sees a brighter future for AWS Solutions Architect over the upcoming years with the expansion of cloud computing worldwide. In a report by Global Knowledge on IT Skills and Salary, the average salary of an AWS certified IT professional turned out to be 30% more than the average salary of an average IT certified expert. With AWS capturing around 41.5% of the cloud computing market, companies are seeking out candidates with AWS certification rather than its competitor brands such as Azure or Google.

Cloud computing is emerging as the backbone of companies, and the promising market trends are attracting more candidates to apply for AWS certifications for a brighter career opportunity. In addition, not only in the US but Globally, AWS setting up cluster data centers has led people to look into various AWS certifications as it draws greater chances for recruiters to consider their profiles over non-certified IT professionals. 

AWS Certified Solutions Architect Salary across the US

AWS is one of the leading figures of the cloud computing market. It delivers great benefits to its certification holders, which is probably why the highest salary for an AWS Solutions Architect is $170K+ per annum. The base salary for an entry-level AWS Solutions Architect lies near $77K a year. Overall, the average salary for an AWS Solutions Architect in the US goes up to $120K a year. The ranging salary numbers increase and decrease according to the skills and experience a candidate brings along with their candidature. 

The salary range is subject to change on a few other factors, including features like degree, work experience, designation, employer brands, and other job profiles in the same domain. However, among all of these factors, the job location is one of the most significant features directly affecting the salary range. 

Work location plays a vital role in defining the salary an AWS Solutions Architect is offered and the amount they are likely to increase in the coming years. Here are some of the regions and their varying annual wages in the US. 

Salary expectations for an entry-level AWS Solutions Architect to experienced ones vary greatly from place to place. The best way to bag an attractive offer at your dream place is to hold the right credentials and certifications. One can even bag a salary hike while working and getting certification at the same time to add value to their resume.  

Essential Skills to Become an AWS Solutions Architect

Being of the top in-demand skills makes AWS Solutions Architect a competitive field, as thought by many, though the lack of candidates with the proper certifications and ample experience makes it hard for recruiters to screen qualified candidates. Fortunately, you can seek a great career opportunity out of this growing market by performing well on eligibility criteria.

Besides holding a bachelor’s degree in a relevant IT domain, there are various other skills an AWS Solutions Architect must have to get through the screening process. Some of them are mentioned here.

  • Proficiency in multiple programming languages
  • Understanding of networking services
  • Fundamentals of data storage
  • Official AWS Certified Solutions Architect – Associate certification
  • Cloud-specific infrastructure and patterns
  • Relevant soft skills

These are some of the key factors an AWS Solutions Architect must have to be eligible for the post. Of course, if you think your resume needs more certifications to bag better opportunities, we have your back!

upGrad’s Executive PG Program in Software Development is an excellent way to strengthen your resume with in-demand skills. IIIT-B offers the program under the vigilance of industry leaders and faculty members to enable learners with up-to-date skills relevant to the market. The course offers specialization in Software Development, Cyber Security, and Cloud Computing to prepare you for the most sought-after career opportunities in the industry. upGrad’s global base of 40000+ learners spread across 85+ nations is proof of their top-notch education services that help learners make progress in seeking and winning better opportunities. 

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.

Conclusion

AWS Solution Architect is a globally sought-after career offering dynamic working solutions and an ever-growing environment to keep up with the market trends. As long as you hold the right set of practical skills with a strong resume, nothing is stopping you from seeking out an exceptionally well-paid position in the market!

Frequently Asked Questions (FAQs)

1. Is a career as an AWS Solution Architect worth it?

The growing market of cloud computing and AWS’s role in the same is increasing demand for candidates eligible to manage the position as AWS Solution Architect. It is a lucrative career for people looking for more opportunities than simply having an average IT professional job. The future awaits a bright career for Solution Architects as the growth of cloud computing is nowhere going down.

2. Can AWS certification increase your salary?

Following basic eligibility criteria, an IT degree, and ample professional experience, the added benefit of an AWS certification can offer any skilled candidate an upper hand over their competitors. As Forbes claims, an AWS certification with your degree can increase your salary by up to $12K a year. It is one of the most in-demand certifications in the market.

3. Which AWS certification is better in today’s time?

The AWS Solutions Architect – Associate is the most in-demand and popular IT certification in the AWS. The reason behind its prominence is the growing cloud computing market. Businesses leverage experts in the field to manage cloud management, right from planning to implementation. An AWS Solutions Architect works effectively to achieve the same and offers great value to the brand with its skills, which is essentially why the wage is exceptionally higher for the position at the same time.

Did you find this article helpful?

Pavan Vadapalli

Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working on solving problems of scale and long term technology strategy.

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With high market demand and a low supply of the right talent, cybersecurity candidates can bag well-paying job roles across different sectors.  Top Jobs with the Highest Cyber Security Salary in the US  As we stated, most cybersecurity roles are accompanied by hefty annual salaries. Here are some of the top positions in the field that you should look out for: 1. Cybersecurity Analyst  The average salary of a cybersecurity analyst in the US is $76,603 per year. Pay in this field starts from $53,000 per annum and goes up to $117,000. Shared profits for this role can go as high as $15,000.  Experience matters a lot here. Entry-level cybersecurity analysts earn 17% below the median, whereas early-career cybersecurity analysts 6% below the average. On the other hand, late-career professionals in this role earn 32% more than the average, while experienced professionals earn 48% more.  A cybersecurity analyst with less than a year’s experience earns $63,000 per annum on average. Similarly, those with one to four years of experience earn $72,000 per annum on average. Experts with five to nine years of experience earn $88,000 per year on average, while those with 20+ years of experience make around $114,000 per annum.  What does a Cybersecurity Analyst Do?  A cybersecurity analyst is responsible for protecting their organization’s systems and network from cyber threats. Thus, they must stay updated with all the industry trends and design contingency plans for different situations.  Cybersecurity analysts review suspicious activities, report security breaches, and train the organization’s staff members on best security practices to safeguard the company’s networks, servers, and systems.  2. Cybersecurity Engineer Cybersecurity engineers earn an average pay of $96,947 per annum. Their salaries start from $67,000 per year and go up to $138,000 per year. Shared profits for this role go up to $12,000, while bonuses may go up to $16,000, depending on various factors.  Entry-level cybersecurity engineers earn 22% less than the average, while late-career ones earn 22% more than the average. Experienced cybersecurity engineers earn 30% more than the average.  Popular skills for this role are security testing & auditing and security risk management.  What does a Cybersecurity Engineer do?  A cybersecurity engineer is responsible for designing and implementing secure network systems for their organization. They have to design solutions that match the company’s unique requirements and protect sensitive data/systems from cyber-attacks and threats. Cybersecurity engineers also have to test and monitor their implemented systems to ensure they operate optimally and protect the network from all the latest threats.  Due to the unique nature of their profession, cybersecurity engineers must continually upskill in their domain and get familiar with the latest developments in the industry.  3. Information Security Officer An information security officer earns an average pay of $92,573 per annum on average. Their salary starts from $59,000 per annum and goes up to $136,000 per annum. Bonuses in this field go up to $21,000 and shared profits go up to $9,000.  A fresher in this field with less than a year’s experience makes $67,000 per annum while those with one to four years of experience $77,000 per annum on average. Similarly, information security officers with five to nine years of experience make $92,000 per annum on average and those with 20+ years of experience make $116,000 per annum on average.  What does an information security officer do? An information security officer is responsible for implementing and monitoring the organization’s security policies, requirements, and compliance. They also oversee the training, policies, practices, and audits to make sure all the systems operate safely and securely. They identify risks by software, role, and information type to define the optimal mitigation strategies.  Information security officers must ensure that the organization’s data remains secure. Thus, they employ effective solutions that prevent hackers or any other malicious technologies from compromising the organization’s data integrity.  Information security officers have to create update schedules and configure the necessary scripts to make the deployment processes faster. They create security checks to help deter malware, spyware, and hackers.  4. Information Security Manager An information security manager earns an average salary of $117,217 per annum on average in the US. Their pay starts from $79,000 per annum and goes up to $152,000 per annum. Bonuses in this field go up to $24,000 while the shared profits can go up to $15,000.  Information security managers with less than a year’s experience earn $84,000 per annum on average while those with one to four years of experience make $94.000 per annum on average. Moreover, professionals in this field with 10 to 19 years of experience earn $122,000 per annum on average.  What does an Information Security Manager do?  An information security manager has to maintain security protocols in their organization. They have to create different strategies for their organization to increase their internet security. They might also have to handle the different cybersecurity implements of their organization’s various projects.  Information security managers are responsible for creating and executing policy, auditing plans, and identifying the security risks their organization faces. They lead the security training procedures at their company and are responsible for communicating the cybersecurity policies.  Information security managers have to help migrate information assets into secure and compliant systems. They also oversee the company’s security testing platforms.  5. Chief Information Security Officer The most revered career in the cybersecurity industry is CISO, also known as a chief information security officer. It is a dream role for many.  The average pay of a CISO in the US is $165,391 per annum. Their pay starts from $105,000 per annum and goes up to $229,000 per annum. CISOs with less than a year’s experience in the field earn $106,000 per annum on average. On the other hand, a chief information security officer with one to four years of experience earns an average salary of $123,000 per year. Those with five to nine years of experience in this role earn $130,000 per year while those with 20+ years of experience make $180,000 per year on average.  What does a Chief Information Security Officer do?  A chief information security officer oversees and monitors the complete cybersecurity infrastructure of their company. They maintain standards, policies, and procedures to protect the integrity and privacy of the organization’s data. CISOs are also responsible for evaluating, reporting on, and suggesting new ideas for safeguarding the company from any potential security threats.  CISOs usually work with a team of cybersecurity professionals to develop the necessary solutions to protect the organization. They also create contingency plans for managing any data or security breaches. In addition, CISOs supervise the development and implementation of security protocols and procedures.  How to Start a Career in Cybersecurity?  If you’re interested in earning a cybersecurity salary, it would be best to enrol in a cybersecurity course. Since cybersecurity roles are highly specialized ones, each with its unique job description and skills, a professional certification program will help you become a job-ready cybersecurity expert. Plus, completing a cybersecurity course will give you the upper hand over your non-certified peers.  The course lasts for 7.5 months and, in the final four weeks, includes a capstone project so you can understand the applications of the skills you learn during the program. You’ll learn the fundamental and advanced concepts of cybersecurity implementations during this program directly from industry experts. This course provides you with 250+ hours of study material and offers 1:1 mentorship sessions with experts.  At upGrad, we offer the Advanced Certificate Program in Cybersecurity in partnership with the International Institute of Information Technology Bangalore. We take pride in the fact that our learner base includes over 40,000 paid learners hailing from 85+ countries. Hence, if you opt for this global course, you will enjoy the experience of peer-to-peer. Not to forget, the course will make you ready to explore job opportunities in the international market.  Conclusion The global demand for cybersecurity professionals is rising because companies are migrating to the cloud and are using more digital technologies to optimize their operations. If you’re interested in pursuing a career in this field, be sure to check out the course we mentioned above.  Although it may seem daunting, bagging a lucrative role in cybersecurity isn’t rocket science. All you need is a passion for upskilling and a little professional guidance from industry experts and mentors. Once you master the fundamentals of the domain and gain the requisite skills, you will have a much better chance of becoming a cybersecurity expert at a reputed organization. 
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by Rohan Vats

30 Jun'21
What is Hashmap in Java? Explained with Examples

5.45K+

What is Hashmap in Java? Explained with Examples

HashMap is a collection class in Java. You can use it to store key and value pairs. Its performance depends on the initial capacity and the load factor. HashMap has various methods that allow you to use its hash table data structure.  In the following article, we’ll explore what HashMap is and learn about its various constructors through examples.  What is HashMap? HashMap is a collection class based on Map. We use it to store Key & value pairs. You denote a HashMap Java as HashMap<K, V>, where K stands for Key and V stands for Value.  HashMap is similar to the Hashtable class. The difference between the two is that HashMap is unsynchronized while Hashtable isn’t. Also, unlike Hashtable, HashMap allows null values and the null key.  Since HashMap isn’t an ordered collection, it doesn’t return the keys and values in the order you insert them. Also, HashMap doesn’t sort the stored keys and values. If you want to use the HashMap class and its methods, you’ll have to import java.util.HashMap (or its superclass). HashMap gives you a simple implementation of Java’s Map interface. You can access the key-value pairs you store through HashMap by using an index of another type (such as an integer). Keep in mind that if you use a duplicate key, it replaces the element of the relevant key. Also, you can only use one null key object; however, there can be any number of null values.  HashMap implements Cloneable, Serializable, Map<K, V> interfaces. It extends the AbstractMap<K, V> class, and its direct subclasses are PrinterStateReasons and LinkedHashMap.  Features of HashMap  Following are the primary features in HashMap:  It is a component of the java.util.package. You can use duplicate values, but HashMap doesn’t allow duplicate keys. It means one key can’t have multiple values, but multiple keys can have a single value.  You can use null keys only once, but you can use various null values.  HashMap provides no guarantees regarding the map’s order. So, it doesn’t guarantee if the order will remain constant.  HashMap is very similar to Hashtable, with the only difference being that HashMap is unsynchronized.  HashMap implements a Serializable and Cloneable interface.  HashMap Constructors There are four constructors in HashMap: 1. HashMap() HashMap() is the default constructor that creates an instance with a load factor of 0.75 and an initial capacity of 16. Example:  // Showing how HashMap() constructor works  import java.io.*; import java.util.*; class AddElementsToHashMap {     public static void main(String args[])     {         // You don’t have to mention the         // Generic type twice         HashMap<Integer, String> hm1 = new HashMap<>();         // Using Generics to initialize HashMap         HashMap<Integer, String> hm2             = new HashMap<Integer, String>();         // Use the put method to add any element         hm1.put(1, “A”);         hm1.put(2, “B”);         hm1.put(3, “C”);         hm2.put(4, “D”);         hm2.put(5, “E”);         hm2.put(6, “F”);         System.out.println(“Results of hm1 are : “                            + hm1);         System.out.println(“Results of HashMap hm2 are : “                            + hm2);     } } Output:  Results of hm1 are : {1=A, 2=B, 3=C} Results of hm2 are : {4=D, 5=E, 6=F} 2. HashMap(int initialCapacity)   HashMap(int initialCapacity) would create an instance with load 0.75 and a specific initial capacity.    Example:   // Showing how HashMap(int initialCapacity) constructor works     import java.io.*; import java.util.*; class AddElementsToHashMap {     public static void main(String args[])     {         // You don’t have to mention the         // Generic type twice         HashMap<Integer, String> hm1 = new HashMap<>(10);         // Using Generics to initialize HashMap         HashMap<Integer, String> hm2             = new HashMap<Integer, String>(2);         // Use the put method to add any element         hm1.put(1, “A”);         hm1.put(2, “B”);         hm1.put(3, “C”);         hm2.put(4, “D”);         hm2.put(5, “E”);         hm2.put(6, “F”);         System.out.println(“Results of hm1 are : “                            + hm1);         System.out.println(“Results of HashMap hm2 are : “                            + hm2);     } } Output:  Results of hm1 are : {1=A, 2=B, 3=C} Results of hm2 are : {4=D, 5=E, 6=F} 3. HashMap(int initialCapacity, float loadFactor)  HashMap(int initialCapacity, float loadFactor) generates an instance with a specific load factor and initial capacity. Example: // Showing how  HashMap(int initialCapacity, float loadFactor) Constructor works import java.io.*; import java.util.*; class AddElementsToHashMap {     public static void main(String args[])     {         // You don’t have to mention the         // Generic type twice         HashMap<Integer, String> hm1             = new HashMap<>(5, 0.75f);         // Using Generics to initialize the HashMap         HashMap<Integer, String> hm2             = new HashMap<Integer, String>(3, 0.5f);         // Use the put method to add elements         hm1.put(1, “A”);         hm1.put(2, “B”);         hm1.put(3, “C”);         hm2.put(4, “D”);         hm2.put(5, “E”);         hm2.put(6, “F”);         System.out.println(“Results of hm1 are : “                            + hm1);         System.out.println(“Results of HashMap hm2 are : “                            + hm2);     } } Output:  Results of hm1 are : {1=A, 2=B, 3=C} Results of hm2 are : {4=D, 5=E, 6=F} 4. HashMap(Map map) HashMap(Map map) would create an instance with the same mappings as the map you specify.  Example: // Showing how HashMap(Map map) constructor works  import java.io.*; import java.util.*; class AddElementsToHashMap {     public static void main(String args[])     {         // You don’t have to mention the         // Generic type twice         Map<Integer, String> hm1 = new HashMap<>();          // Using Generics to initialize HashMap         HashMap<Integer, String> hm2             = new HashMap<Integer, String>(hml);         // Use the put method to add any element         hm1.put(1, “A”);         hm1.put(2, “B”);         hm1.put(3, “C”);         hm2.put(4, “D”);         hm2.put(5, “E”);         hm2.put(6, “F”);         System.out.println(“Results of hm1 are : “                            + hm1);         System.out.println(“Results of HashMap hm2 are : “                            + hm2);     } } Output:  Results of hm1 are : {1=A, 2=B, 3=C} Results of hm2 are : {4=D, 5=E, 6=F} Learn more about Java Java has many classes apart from HashMap. Learning about the nitty-gritty of each of those classes, their uses, and integration in Java by yourself is pretty challenging. The best way to go about this process is by taking a computer science course. Taking a professional course will enable you to master the necessary skills and concepts through a structured curriculum. Furthermore, such courses offer an immersive learning experience facilitated by videos, live sessions, and online lectures that make it easier for you to understand theoretical fundamentals. You can check out our Master of Science in Computer Science program offered in association with LJMU (Liverpool John Moores University, UK) and IIIT-B (International Institute of Information Technology, India). The course covers 500+ hours of content, 10+ live lectures, and 30+ case studies. This 19-month course promises a highly value-oriented and global learning experience. The biggest value addition lies in the fact that you get to connect and engage with peers from across the world. upGrad boasts of having 40,000+ paid global learners spread in over 85+ countries.  As a result, you are exposed to new cultures, new opinions, and new perspectives that broaden your overall outlook. Not just that, you are trained by expert mentors from LJMU and IIIT-B who deliver dedicated and personalized assistance to help resolve your doubts.  Along with these advantages, this program will provide you with 360 degrees career assistance that includes industry mentorship, networking opportunities, and much more.  Conclusion In this article, we learned what HashMap is, its different constructors, and how you can implement them through examples. HashMap has a ton of applications in Java – you can use HashMap to add items, remove them, and manage them as required.  What are your thoughts on this guide on HashMap? Share them in the comment section below. 
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by Arjun Mathur

02 Jul'21
Scrum Master Salary in US in 2024

6.77K+

Scrum Master Salary in US in 2024

The job role of a Scrum Master started gaining prominence from 1992 onwards when Jeff Sutherland and his team coined the term. From then to now, Scrum Master has established its importance to organizations across the globe and has grown to become one of the higher paying and most promising jobs in the current times.  In this article, let’s look at a Scrum Master’s salary along with the factors that affect this salary range!  Factors influencing a Scrum Master’s salary range Here are some factors that go on to determine your salary as a Scrum Master:  1. Years of Experience  This is easily one of the most important criteria that influence the final salary that you’ll draw as a Scrum Master. With experience, the job roles and responsibilities taken by Scrum Master increase, and so does the salary figure. Here are some things that Scrum Masters learn with experience, that influence their salaries:  If you’re aiming to bag a higher-paying Scrum Master job, it’s recommended that you work as a Scrum Master for a minimum of one year and apply different Scrum practices, theories, and principles.  Understanding leadership principles, facilitation, conflict resolution, situational awareness, continual improvement, and more.  2. Level of Skills and Responsibilities Required for the Job A Scrum Master’s job isn’t bound to a particular designation. The more experienced you are (and if you have considerable experience working in agile teams), the better idea you’ll have about the latest Scrum strategies around problem-solving. These approaches include XP, Crystal, Kanban, FDD, etc. If the job role requires you to handle multiple tasks using different technologies and strategies, you can expect a higher salary package.  To get better job opportunities, it is preferred to have knowledge of different successful Agile techniques such as: TDD ATDD Continuous integration Continuous testing User stories Automated testing Pairing Agile games  3. Applicable Knowledge of the Underlying Technologies An organization is likely to offer you higher salaries as a Scrum Master if you have a working understanding of the technology that powers their business. That’s simply because if you’re aware of their technologies, they won’t need to spend time, effort, and resources in helping you train in that particular technology – and that way, they’ll be in a position to offer you higher salaries.  4. Knowledge of Appropriate Patterns and Techniques A professional Scrum Master always utilizes various well-documented techniques and patterns for filling in the intentional gaps left in the Scrum approach. These approaches include things like various retrospective formats, burndown technologies, handling bugs, and more. If you’re aware of these techniques and have a working knowledge of them, you’ll find yourself in a position of demanding higher salaries.  5. Location of the job This one goes without saying. The final salary that you’re offered for the Scrum Master role by any organization depends largely on where the job is located. If it’s a city with high living standards and a dense population, the salary offered is generally higher as compared to if the job is in a remote city with lower living standards.  Salaries Offered to Scrum Masters According to Payscale, the average salary for entry-level Scrum Masters in the USA is $79,309 per year. This figure goes on to touch the six-figure mark of $107,957 in some organizations and roles. However, with more experience and skills, the salaries become increasingly better. Payscale indicates that a Scrum Master with 3-5 years of experience in the USA can, on average, earn $103,566 yearly, with this figure reaching as high as $134,203 yearly for some organizations. If you have over 5 years of experience and possess the latest industry skills required to work in an agile team, your salary range will increase inevitably. With 5+ years of experience, Scrum Masters in the USA can on average expect a salary of $140,000 yearly. This figure only goes higher from here with your experience, expertise, and skillsets.  Below mentioned are statistics from Payscale: Scrum Master Experience/Country USA Entry-Level Scrum Master $79,309 p.a. ($107,957 highest) Mid-Level Scrum Master $103,566 p.a ($134,000 highest) Experienced Scrum Master $140,000+ p.a. A 2019 research conducted by Glassdoor revealed that Scrum Masters are among the highest paid professionals in the USA with the overall average salary being $98,000 and the number of vacancies as high as 1,896. In terms of job location, cities such as Atlanta, NYC, Charlotte, Richmond, and Charlotte are among the best to be working as a Professional Scrum Master.  One more factor that goes into improving your Scrum Master salary is the certifications that you’ve done. In that regard, here are some popular Scrum Master certifications and the average salaries that you can draw yearly after completing that certification.  Certified Scrum Master – $89,000 Professional Scrum Master – $90,000 Agile Certified Practitioner – $105,000 Agile Scrum Master – $110,000 Scrum Master Certified – $110,000 SAFe Scrum Master – $115,000 Top Companies that Hire Scrum Masters Scrum has become increasingly popular in the past few years, with a greater number of software industry leaders adopting its techniques for solving their day-to-day challenges. According to the Scrum Guide, most software development companies across the world use Scrum strategies in some shape or form. Before reaching the software development industry, Scrum had already been adopted for industries like operations, education, marketing, manufacturing, and others.  If you have the required experience and expertise to deal with conflicts and are a proven facilitator, you’ll find many top companies hiring for the position of Scrum Master. According to Glassdoor job results, here are the major companies hiring Scrum Masters in the USA, along with the average yearly pay that you can expect at these organizations:  TransUnion – $104,000 Thomson Reuters – $103,000 UnitedHealth Group – $97,000 Ciber – $97,000 IBM – $94,000 J.P. Morgan – $92,000 Capital One – $87,000 AT&T – $85,000 The past few years have seen the pay structure of Scrum Masters increase at a rapid pace. Even today, the popularity of Scrum Masters continues to increase. So, if you like working in an Agile environment as in situations of conflict resolution, you might be just the right fit for working as a Scrum Master. The job role is broadly all about using Agile-Scrum techniques to take the projects to completion on time without compromising on the quality of work.  Why is Scrum Masters so Highly Paid? Scrum methods have brought revolutionary changes in the way project management was accomplished in various organizations. Problem-solving and conflict resolution have been simplified beyond measures by deploying Scrum methodologies. This reason alone is enough to justify the high salary that Scrum Masters tend to draw.  We’re living in the digital age where products and software need to be delivered on time after continuous feedback, revisions, collaboration, and so much more. To keep all things in control and ensure that the product rollout happens on time, it’s essential for all the different teams to work in sync. That sounds easier than done – and that’s why Scrum Masters are there to keep everybody on the same table while working towards a common goal.  Companies today, regardless of their domain of operations, are highly aware of the importance of an Agile workflow and a Scrum Master. Scrum Masters can take any team and convert it into a self-organized, productive unit by following Scrum practices, and that is what makes them unique and indispensable for any organization.  In Conclusion Scrum Masters are professionals that are paid handsomely no matter the organization they work for. If you look at their roles and responsibilities, this will make complete sense to you.  After all, they’re responsible for seamless end-to-end project management in the most efficient manner.  The good news is that becoming a Scrum Master is not that difficult. If you’re inherently a curious person with an inclination towards conflict resolution, this is just the perfect job for you, and with just a little bit of guidance and support, you’ll be on your way to working as a Scrum Master in an organization of your choice.  So, if you’re a beginner in this Agile world and are looking to get yourself a solid foundation, we recommend you check out the Master of Science in Computer Science course. Whether you’re a fresher or a mid-level expert or a senior-level professional – this course is designed to offer something to everybody. Check out the curriculum and know more for yourself! If you’re looking for a career change and are seeking professional help – upGrad is just the upskilling platform for you! We are proud to have a learner base spread across 85+ countries, 40,000+ paid learners globally, and 500,000+ happy working professionals. Our 360-degree career assistance, combined with the exposure of studying and brainstorming with global students, allows you to make the most of your learning experience. Reach out to us today for a curated list of courses around Data Science, Machine Learning, Management, Technology, and a lot more! 
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by Rohan Vats

09 Jul'21
What is React? A Complete Overview

5.28K+

What is React? A Complete Overview

What is React? React is an open-source, component-based JavaScript library used to create quick and interactive interfaces or UI components for users for web and mobile-based applications.   Ever since its release in 2013 by Facebook, React, a JavaScript library used to build web applications, has consistently witnessed an upward trend. It is now the most-used JavaScript library alongside the likes of jQuery, Vue, and Angular. It is a declarative and highly accurate library that provides reusable code, which enhances the efficiency and flexibility of single-page applications.  Its key features are SX and Virtual DOM, which set it apart from other JavaScript libraries. Popular companies like Facebook, TripAdvisor, and Airbnb are users of React. Key Highlights of React The component-based, front-end library optimizes the page loading speed and efficiency of single-page applications. React helps in generating easy-to-use interactive UIs. It is used to design comfortable and interactive views for every state in the application. It offers on-time updates that help users to receive relevant components required when data changes. React breaks the UI into smaller individual components, enabling users to simultaneously work on each component resulting in faster app development. Why does React have the edge over other frameworks? React has a lot of efficient features that make the library stand out against other libraries. The following is the list of powerful features that have catapulted React to the numero uno position: Effective DOM Manipulation DOM (Document Object Model) is a crucial part of the web application, as it represents the web page of a document, generally HTML. DOM manipulation has become the latest trend in modern applications as they require numerous animations, state transitions, impactful effects, and so on:  The Virtual DOM is a virtual model of the actual DOM tree with each branch ending in a node that contains objects. The feature enables the users to update only the necessary parts of the DOM tree instead of re-rendering the entire UI. The whole process of implementing a virtual DOM is faster as it stays only in the memory without providing access to the user. JSX The JavaScript’s syntax extension is merged with React to clearly define how the user interface (UI) is supposed to look. JSX can be used to write HTML structures in a file that has JavaScript code. By doing this, the code becomes easily understandable as the process avoids complex JavaScript DOM structures. More functionality with lesser code React facilitates the simple and quick generation of dynamic web applications as it requires less coding against JavaScript that involves complex coding. Quick application development Components are the foundation of any React application. Most apps require a lot of components to control each task in app development. React components have a wide range of logic and controls that can be reused because of which the applications can be developed at a quick pace. Easy error debugging In React, the child components are placed inside the parent components, and so the data flows only in one way. The single direction of data enables the app developers to identify the exact location of the error in an application resulting in faster debugging. React components are designed based on the Separation of concerns principle, according to which a computer program is separated into smaller sections, each of which addresses different issues. Use of UI component library A set of ready-made components that provide the necessary blocks of code for developing apps constitute the UI component library. The use of the UI library, Kendo React, brings in a lot of advantages like greater compatibility, better accessibility, speed, and easier handling. For instance, the Create React app is used at the beginning stage of React app setup. This enables the developers to start using the React app with a single command.  Redux Redux is a popular state management library used in React. It places all the data inside a store such that each component has access to the store. The two powerful concepts of Redux are actions and reducers.  Actions are the events that transfer the data, and reducers are functions that perform a task corresponding to the data and return it to a new state. Easy to learn It is easy to learn React as it is an amalgamation of HTML and JavaScript concepts with some add-ons. Use in developing mobile apps  React is known for its effectiveness in web application development but is not limited to only that. React Native, an immensely popular framework of React helps in developing mobile applications.  Chrome extension to debug React applications Facebook has come up with a chrome extension that is exclusively used for debugging React applications. This makes debugging simpler and faster. The above features make React one of the most-used JavaScript libraries, which are preferred by a huge number of businesses over the likes of jQuery, Vue, and Angular.  In addition to this, React does not insist on strict code conventions or file organizations, unlike other frameworks. This helps developers to have their convenient conventions and use React in any way they like. React can be assigned to handle a single button, a few interface pieces, or an application’s entire user interface.  Prerequisites for learning and using React The following list will help developers who have just started using React determine if they are ready to take the plunge: A basic understanding of HTML, JavaScript, CSS, Babel, and Package manager: Front-end developers should know how to generate CSS selectors, HTML tags and to develop applications using HTML and CSS. A good grip on ES6, JSX, and their features: In React, the developers need to use JSX that gives the flavour of HTML JavaScript. A complete understanding of how to use JSX is mandatory to learn React. Understanding of how Node Package Manager (NPM) works: A basic understanding of installing packages using NPM, finding required software from the NPM registry is indispensable for developing React apps.  React Vs. Angular and Vue Angular, developed by Google in 2010, is a TypeScript based framework. Two versions of the same were released in 2016 (Angular 2) and 2020 (Angular 11). Vue, a.k.a Vue.js, was released by Evan You in 2014. The latest version of Vue was released in September 2010 (Vue 3.0), which has its own GitHub tool.  Let us compare the key aspects of the three frameworks.  Key features React Angular Vue Year of release 2013 2010 2014 Website Reactjs.org Angular.io vuejs.org Latest Version 17.x 11 3.0.x Leading companies using the framework Facebook, Uber Google, Wix Alibaba, GitLab Number of Contributors 1533 1352 382 Number of jobs in LinkedIn 70963 72747 11590 Future Scope of React in the Industry With growing patronage from new-age developers, React has become a top trend in the front-end development industry.  React developers are better compensated than other web developing frameworks. According to PayScale, the average salary offered to developers in React.js is $92,341 per year. Compensations increase as you level up in your career — L4 Lead Front End Engineers are paid a high base salary of $115,862 per year. It is widely preferred by many companies owing to its simplicity and quick pace and so React developers have a huge demand in the market. Many leading companies like Facebook, PayPal, Instagram, UBER, and Airbnb use React for their web development. Therefore, React developers have a potential future as the technology is used in a wide range of industries. Ever since its release in 2013, React has been consistently growing in demand and popularity and Facebook adding many advanced features to the tool is making it more desirable and stronger in the market. ReactJs has completely revamped the front-end handling making it faster and easier by addressing its view issue and providing a UI view and storage layer. Let us look at the key parameters of React that show its current trend in the market: Key Parameters Figures of React Number of Watchers 6,700 Number of Stars 16,400 Number of Forks 32,900 Number of Contributors 1,533 React is also comparatively easier to learn and has a wider community than other libraries like Angular or Vue. The job market for React developers looks very promising.  The following table shows the number of positions available for React developers: List of job portals Number of Vacancies LinkedIn 70963 Indeed 14595 Simply Hired 10508 Dice 3529 AngelList 4383 Hired 9 Remote 1136 To Conclude The path to learning React might take time, but it is certainly worth the effort and time given its popularity as the most-used JavaScript for developing modern applications. The powerful and efficient features of React and the ease of handling them make it unique from other libraries and frameworks. The tools introduced by React like JSX, DOM, and reusable components have completely revolutionized and simplified the process of app development.  All the above features make ReactJs an indispensable tool in web development. Developers who look beyond Angular and Vue find React as their one-stop destination. According to The State of JavaScript 2020 survey, React tops the list of most-used JavaScript libraries, which proves that this framework is here to stay for a long time. Enhance your skills with a Master’s in Computer Science If you’re looking for more detailed information on React or related software and tech subjects, here’s upGrad’s Master of Science in Computer Science for power learning online from IIIT Bangalore & LJMU.  The course comprises six Executive PGP specializations: Full Stack Development, Cloud Computing, Cyber Security, Big Data, Blockchain Development, and DevOps — each of which is supplemented by top-notch learning content, case studies, and industrial projects, and live sessions.  Freshers to mid-level and senior-level software engineers have an incredible opportunity to enhance their skillset and pursue higher-level job roles without quitting their current jobs.  The 19-month course grants students IIIT Bangalore & LJMU alumnus status apart from providing them access to upGrad’s 40,000+ paid learner base. Students can pursue networking and peer learning on a global level by connecting with professionals spread across 85+ countries. Students also receive 360-degree career assistance from industry experts and leading faculty through upGrad’s online programs.  This is your chance to uplevel and transition to Software Development roles. So, start your learning journey today!
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by Rohit Sharma

28 Jul'21
A Complete Python Cheat Sheet (Updated 2024)

7.17K+

A Complete Python Cheat Sheet (Updated 2024)

The United States has the largest number of software developers specializing in technologies like Python. If you want to be one of them, it is best to start with the fundamentals. We have compiled a Python cheat sheet below to kickstart your learning journey! Applications of Python As a leading general-purpose programming language, Python is used for a wide range of industry applications.  Here are some of its popular use cases: Web development is backed by frameworks like Django, Pyramid, Flask, and content management systems such as Plone. Scientific and numeric computing powered by SciPy, Pandas, IPython, etc. Desktop GUIs enabled by toolkits like Livy, wxWidgets, PySide, and GTK+. Software development, including build, control and management, and testing. Programming-related education and training, both at the introductory and advanced levels. Business applications encompassing ERP and e-commerce solutions. Examples of enterprise application platforms include Odoo and Tryton.  In terms of technical skills, Python lets you master two coding tasks at once, i.e., server-side development and machine learning. It is open-sourced, equipped with extensive libraries, and supports user-friendly data structures. Moreover, you can easily find a Python cheat sheet pdf online to clarify the basics.  The following Python cheat sheet will familiarize you with the data types, math operators, strings, functions, lists, and tuples. We have also included Regular Expressions (Regex) information to give you a well-rounded view of the programming language.  Getting Started with Python The first step is to check whether your computer has pre-installed Python. You can do so via the Command Line search. After that, you can begin writing your code in any text editor and save the file in .py format. You would then be able to run the code in the Command Line prompt.  However, this approach is suitable only for straightforward, non-data science tasks. You might want to switch to IDE or IDLE if you want to interpret your code. If you are a beginner in python and data science, upGrad’s data science online courses can definitely help you dive deeper into the world of data and analytics. IDLE stands for Integrated Development and Learning Environment. Every installation comes with a Python IDLE that highlights relevant keywords or string functions. Shell is the default mode of operation that lets you test various code snippets via the following tasks:  Read statements Evaluate results Print results on the screen Loop to the next statement  Data Types in Python A Python value is termed an “object.” Every object has a particular data type. Here is a list of the most-used data types with examples: Integers: Represented by keyword (int), it includes integer numbers, such as -2, -1, 0, 1, 2, etc. Floating-point numbers: Non-integer fractional numbers denoted by (float). For example, -1.5, -1, -0.5, 0, 0.5, 1, 1.5 Strings: Sequence of characters that cannot be changed once defined. For example, “hello”, “hey”. Typically, single, double, or triple quotes are used to create a basic Python string.  Whichever option you choose, keep it consistent throughout the program. Here are some other things to keep in mind: The print() function would output your string to the console window.  You can apply join() or replace() to modify these strings but cannot rewrite the original.  Lists: Ordered sequence of elements that keep the data together so that you can perform operations on several values at once. Each value is termed as an “item” and placed within square brackets. The items can be changed once stored. Consider the examples below. one_list = [1, 2, 3, 4] two_list = [“b”, “c”, “f” “g”] three_list = [“4”, d, “car”, 7] Tuples: Similar to lists, but the stored values cannot be changed. You can create a tuple as follows: new_tuple = (5, 6, 7, 8) my_tuple[0:5] (2, 3, 4) Dictionaries: Indexes that hold key-value pairs. It can include integers, boolean, or strings. For instance, Buyer 1= {‘username’: ‘john doe, ‘online’: true ‘friends’:150}  You can use the any of these two options to create a dictionary: my_dict = {} new_dict= dict()  Let us now look at the common practicalities of these data types.  String Concatenation & Replication Concatenation involves adding two strings together with the “+” operator, as demonstrated below. my_string = “I love” other_string = “reading books” final_string = my_string + other_string Notably, concatenation is only possible for the same data types. If you try to use “+” for a string and integer, you will encounter an error in Python.  The replication command lets you repeat a string using the * operator.  ‘Alex’ * 4 ‘AlexAlexAlexAlex’ print(“Alex” * 4) However, this only holds true for string data types. When * is applied to numbers, it acts as a multiplier, not a replicator. Math Operators You can apply several math operations with numbers via specific operators. For reference, let’s examine this list: To return an exponent, use “**” (2 ** 4 = 16) To multiply numbers, use the single asterisk sign, “*” (2 * 2 = 4) To get the quotient in integer division, use “//” as the operator (20 // 8 = 2)  For the remainder, apply the “%” symbol (20 % 8 = 4) For the floating point number, apply “/” (20 / 8 = 2.5) For subtraction, “-” is the standard operator (6 -2 = 4) To add numbers, use “+” (3 + 3 = 6) Functions in Python Functions are blocks of coded instruction capable of performing particular actions. Python has some built-in functions, namely:  Input(): Prompts the user for input, which is further stored as a string.  len(): Finds the length of strings, lists, tuples, dictionaries, and other data types. filter(): Excludes items in iterable objects, such as lists, tuples, or dictionaries.  You can also define your own function using the def keyword followed by name():. Here, the parentheses can either stay empty or contain any parameters to specify the purpose of the function.  Performing Operations with Lists  The list() function provides an alternate way of creating lists in Python. The statements mentioned below illustrate this option.  my_list = list ((“1”, “2”, “3”)) print(my_list) The append() or insert() functions are used to add new items to a list. Functions like remove() and pop() let you remove items from a list. Alternatively, you may try the del keyword to delete a specific item. The “+” operator combines two lists, and the sort () function organizes the items in your list.  Working with ‘If Statements’ Python supports the basic logical conditions from math:   Equals: a == b Not Equals: a != b Less than: a < b Less than or equal to a <= b Greater than: a > b  Greater than or equal to a >= b  You can leverage these conditions in various ways. But most likely, you’ll use them in “if statements” and loop. The goal of a conditional statement is to check if it’s True or False. if 5 > 1: print(“That’s True!”) Output: That’s True! You can know more about Nested If Statements, Elif statements, If Else Statements, and If-Not statements in any Python cheat sheet pdf.  Creating Python Classes Every element, along with its methods and properties, is an object in Python, considering it is an object-oriented programming language. Classes are blueprints for creating these objects. While a class is manifested in a program, objects are the instances of the class. Suppose you have to create a SampleClass with a property named x. You will begin with: class SampleClass:  z = 4 In the next step, you will create an object using your SampleClass. You can do so using p1 = SampleClass(). You can further assign attributes and methods to your object with a few simple steps.  Python Exceptions (Errors) Here is a list of some common errors that pop up while using Python.  KeyError: When a dictionary key doesn’t feature in the set of existing keys. TypeError: When an operation or function is inapplicable to an object type. ValueError: When a built-in operation or function gets an argument with the correct type but of inappropriate value.  IndexError: When a subscript cannot be detected, being out of range.  ZeroDivision: When the second argument of a division operation is zero. AttributeError: When an attribute assignment fails. ImportError: When an import statement fizzles in locating the module definition. OSError: A system-related error. For troubleshooting these errors in Python, you can use exception-handling resources — try/except statements.  Python Regex Cheat Sheet Regex is an integral part of any programming language. It helps you search and replace specific text patterns. In other words, it is a set of characters that lets you remember syntax and how to form patterns depending on your requirements. So, let’s look at some useful regex resources for Python.  Basic characters ^ matches a string expression to its right before the line break $ matches the expression to its left before the string experiences a line break xy matches the xy string. a|b matches the a or b expressions. b is left untried if a gets matched first.  Quantifiers + matches an expression to its left once or more than once. * matches an expression to its left 0 or multiple times. ? matches an expression to its left between 0 and 1 time.  {p} matches an expression to its left not less than p times. {p,q} matches an expression to its left between p and q times.  {p,} matches an expression to its left p times or more than p times.  {,q} matches an expression to its left through q times.  Module Functions re.findall (A, B) returns a list of all instances of expression A in the B string.  re.search (A, B) returns a re-match object of the first insurance of expression A in the B string.  re.sub (A, B, C) replaces A with B in the C string.  You can find more regular expressions on character classes, sets, and groups in any Python regex cheat sheet available online.  Summing up In this blog, we detailed the foundational steps of working with the Python programming language. We covered everything from IDLE to integers, strings, lists, dictionaries, tuples, and math operators. We also learned how to define a function and discussed examples of different statements and errors. By no means is the above checklist complete, but it can definitely help you get the hang of Python. Once you are through with these nuts and bolts, you can increase your speed and productivity with regular practice.  Additionally, Python’s active support community and advanced online courses can help you stay updated. Check out upGrad’s Executive PG Program in Software Development and other programs in technology, data science, and machine learning. The platform allows the flexibility to learn at your own pace, a benefit that is celebrated in over 85 countries. upGrad courses have transformed the career trajectory of more than 40,000 paid learners and 500,000 working professionals globally. Perhaps the above Python cheat sheet would fuel your curiosity to explore and upskill! 
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by Rajat Gupta

09 Aug'21
What is React? Definition, Function &#038; Applications

5.35K+

What is React? Definition, Function &#038; Applications

What is React? React is an open-source JavaScript collection that is known to construct highly responsive and dynamic user interfaces. Thus, ReactJS emerges as a very effective solution for creating scalable mobile apps and front-end web with its classic component-based design. You can even build reusable UI components with React. Jordan Walke developed React while working with Facebook as a software engineer. It was available in the public eye in 2011 on Facebook and later in 2012 on Instagram. React primarily focuses on building interactive, appealing, and natural applications. Moreover, it can provide you with the best rendering performance with just basic coding. React allows developers to create an extensive web application that can transform data without reloading the page. You can view this in the MVC template and can be used by combining other JavaScript frameworks. Many top companies like Airbnb, Netflix, New York times, and Instagram have used React. It has also been instrumental to frameworks like Angular.js. React has some remarkable features like server-side rendering, real-time updates, and so on. Fortunately, this JavaScript library doesn’t fail to impress anyone. If you’re new to React framework or just refreshing your core concepts, we are here to provide you with all the fundamentals of React library. To know more, you may like to read further! Key Features of React React JavaScript has a huge fan base in the developers’ community for its robust features. Some of its distinguishing features are: 1. Virtual DOM This is a core feature of React, as it facilitates flexible and fast application development. Furthermore, it enables React to replicate a web page in its virtual memory with its memory reconciliation algorithm. So, a virtual DOM is represented instead of the original DOM. The virtual DOM re-renders the complete user interface with every modification in the application. Point to note, only the components that changed are updated, and the rest of the components remain the same in virtual representation. Thus, React helps to make the development process cost-effective and quick for the developers. 2. JavaScript XML JavaScript XML is popularly known as JSX. It is a syntax that is quite similar to HTML. It is primarily used to describe the appearance of an application UI. It is one of the critical features that ReactJS offers to developers. It injects components identical to HTML in the web page to create the syntax. This helps to make writing the building blocks of ReactJS effortless. It also allows the developers to create syntax most easily. 3. One-way data binding React offers one-way data flow, which creates one of the primary reasons for its easy work management. Unidirectional data binding is used in ReactJS, which means that the developers can not edit any component directly. However, they have to operate through the call-back function to make any changes. Hence, its process of work is called one-way data binding. ReactJS uses Flux(a JavaScript application) to perform data control from a central point. Thus, developers can easily manage mobile applications and the web. Moreover, it enhances efficiency and makes the application more flexible. 4. React Native React Native is customized to use native components instead of web components. In addition, it renders react-native format for ReactJS. Therefore, one should be very accurate and precise with the concepts of ReactJS to acquire the understanding and principles of React Native. These include props, state, jsx, and components. React Native changes the react code to make it compatible with iOS and Android platforms. It also aims to provide access to native features of this platform to the developers. 5. Declarative UI Declarative Ul is a feature that generates a simple view of the application and helps create engaging mobile applications. It enables an interactive user interface for web and mobile applications. ReactJS adequately updates just the right components with the help of this feature to have proper data modification. This feature enables to make code more readable while also simplifying debugging. 6. Component-based Architecture From the above features highlighted, it is clear that the architecture of ReactJS is a component-based platform. It is divided into multiple components wherein each component has its unique ability and specific logic. Component-based architecture proclaims that React is written in JavaScript and not by using a template. So, developers can walk through the application without affecting the DOM. Component, Props, and State 1. Components Components are considered as the basic creating blocks of any ReactJS application. To be precise, a single application generally consists of multiple components. It is the most critical piece of the user interface. It helps to separate the UI into reusable and independent parts that can quickly be processed. Components are classified into two main domains, which are as follows: Functional Component Functional components are simply represented by a presentational function. This function takes props and changes a React element to render it to the page. Mostly, whenever possible, it is preferred to use functional components because they are predictable and concise. Furthermore, as it is purely presentational, the output is always the same as the props. The functional component is also referred to as stateless, presentational, and dumb. All these names are obtained from the nature that functional components take on: Stateless, as they do not hold or manage state. Presentational, as the all put output as UI element. Functional, as they are basic functions and nothing else. Example of functional component: const Greeting = () => <h1>Hi, I’m a dumb component!</h1>; Class Component Class components are built by using ES6 class syntax. Additionally, they have features like the ability to contain logic, local state, and few other capabilities. These components are considered to be a container or stateful and smart: Class, as they are basically divided into categories. Stateful, as they can hold and manage local state. Smart, as they contain logic. Container, as they contain or hold numerous other components. Class components have a large markup and are the opposite of functional components. If you use them more than required can affect the performance of the code testability and readability. The simplest form of class component: class Greeting extends React.Component {    render(){      return <h1>Hi, I’m a smart component!</h1>;    } 2. Props Props are enabling components of ReactJS to be dynamic and easily customizable. They are the way to provide data from one computer to the other – it is a unidirectional data flow. Components can accept and return props customized React elements based on the props received. Props are read-only, components that must never modify the props passed to it. So, for example, the same component should be given as output and input. 3. State The state is an integral React element which uses contain information or data about the component. Over time the state of the component can be changed; whenever it changes, it leads to the rendering of the component. The change can happen due to the response of user action or system-generated events. These changes define the component and how it will render. Wrapping up React offers plenty of flexibility to developers by simplifying the development process. Thanks to React Native, you can “Learn once, write anywhere.” Thus, once you understand React’s fundamental architecture and principles, you can design fully functional web and mobile applications. The fact that React has an active support community makes it an even more attractive choice for developers – you will always find someone to navigate you through app development challenges.  If you wish to master the nitty-gritty of React and other such trending industry tools, you should definitely check out upGrad’s Software Technology courses. upGrad promises overall development powered by peer-to-peer learning across a global learner base of 40,000+ students. Apart from a well-structured curriculum, learners enjoy interactive live sessions with top instructors and industry experts.
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by Pavan Vadapalli

12 Aug'21
Python Append Function: Why, What?(With Examples)

7.15K+

Python Append Function: Why, What?(With Examples)

Python is a vast programming language with numerous applications and libraries. No wonder it is the most popular and widely used programming language by developers globally. What makes it a versatile language are its English-like syntax and the extensive range of functionalities that accompany it.  One of those functions is the Python append function, which we’ll talk about today. You’ll learn what the append function is, why it’s so important, and what makes it unique. Learn data science to know more about various python functions.  Why is the Python append function important? The append function plays a crucial role in Python when you are working with lists. To understand how it works, you must know why it’s so important and get familiar with the objects it interacts with. We use the Python append function with lists. They are pretty similar to the arrays and don’t necessarily have to be of the same data type. That’s why lists are among the most popular and robust tools in Python. The primary difference between lists and arrays lies in the former’s ability to use multiple data types. A list can have integers, strings, and other lists in itself, and that’s not possible with arrays. Moreover, lists are mutable. In other words, you can modify a list even after you have created it. Python lists are indexed and have a definite count during the initialization process. The system indexes the elements present in a list according to a fixed sequence. The indexing process starts with 0 being the first index while the last item’s index is n-1, where n stands for the number of items present in the list. Every element in a list has an indexed place. This feature allows you to duplicate the elements present in the list as you can repeat an element in the list because both of them would have a different index to distinguish between them. This feature is not present in sets, which is why lists are widely popular in Python implementations. We create lists in python by utilizing [] brackets. You’d have to use commas to separate the elements present in the list. Here’s an example of a list in Python: Input:  first_list = [‘upGrad’, ‘is’, ‘fun’] print first_list Output: [‘upGrad’, ‘is’, ‘fun’] In the above list, the index of the item ‘upGrad’ is 0. You can use the len() function to find the index of a list: Input:  len(first_list) Output:  3 Certainly, lists are versatile objects with numerous potential applications. However, if you wanted to add an item to a list after its creation, what would you do? This is where the Python list append function comes in. Let’s understand that in detail in the next section.  What is the Python append function? The append function adds its argument to a list. More precisely, it adds a single element to the end of a specific list and increases the length of the same by one.  The append function allows you to add an item to the end of the list. It adds the element regardless of its data type. Hence, you can add a string, number, or even another list to the end of the particular list by using this function. The syntax of this function is: list_name.append(element) The input parameter of the append function is one item, and it would add it to the end of a particular list. Also, because it only adds an item to an existing list, it doesn’t have any return value. Examples of Python list append Here are a few examples of how we use the Python list append function with different data types: 1. Adding a number to a list with append function Here’s how we add a number to a list by using this function: Input:  # create a list of strings first_list = [‘upGrad’, ‘is’, ‘fun’] # add an integer item to first_list first_list.append(1) # print the new list print(first_list) Output: [‘upGrad’, ‘is’, ‘fun’, ‘1’] 2. Adding a string to a list with append function You can also use the append function to add a string to a list: Input:  # create a list of strings first_list = [‘upGrad’, ‘is’] # add a string item to first_list first_list.append(‘fun’) # print the new list print(first_list) Output: [‘upGrad’, ‘is’, ‘fun’] 3. Adding a list to a list with append function The append function can add a list to another list as an element: Input:  # create a list of strings # and another list to append to the first one first_list = [‘upGrad’, ‘is’, ‘fun’] second_list = [1, 2, 3, 4] # append second_list to first_list first_list.append(second_list) # print the new list print(first_list) Output: [‘upGrad’, ‘is’, ‘fun’, [1, 2, 3, 4]] Append vs. extend functions  A common point of confusion among Python beginners is about the difference between the append function and the extend function. Both of them extend the length of a list however the main difference lies in the number of elements they add to a list at a time. The append function adds one item to the end of a list. On the other hand, the extend function iterates over the argument and adds every element of its list to the specific list. With the append function, the index of a list increases by one but with the extend function, it increases by the number of elements present in the function’s argument. The append function works with various data types, but the extend function works with lists only. Here’s a pair of examples to explain their difference better. In the first case, we will use the extend function with first_list and second_list, while in the second case, we’ll apply the append function: Input:  # We’ll use the extend function # each element of the iterable will be appended # to first_list first_list = [‘upGrad’, ‘is’] second_list = [1, 2, 3, 4] first_list.extend(second_list) print first_list Output:  [‘upgrad’, ‘is’, 1, 2, 3, 4] Input:  # Here, we’ll use the append function # the list will be added as an element # to first_list first_list = [‘upGrad’, ‘is’] second_list = [1, 2, 3, 4] first_list.append(second_list) print first_list Output: [‘upGrad’, ‘is’, [1, 2, 3, 4]] As you can see, the extend function added the elements present in second_list to first_list, and every item present in second_list became the element of first_list. On the other hand, the append function added second_list as an element to first_list. With the extend function, the length of first_list increased by four elements. However, the append function increased the length of first_list only by one. This is the primary difference between the Python append function and the extend function. Become an expert in Python and related technologies The append function is one of the many functionalities present in Python. If you’re interested in becoming a Python expert, you’d need to familiarize yourself with the various functions and objects it works with. There are many applications of this programming language as it houses one of the largest collections of libraries and frameworks. Numpy, Scipy, and OpenCV are some of the most popular Python libraries. For example, if you pursue a career in machine learning and artificial intelligence, then you’ll enjoy using OpenCV Keras and Scikit-learn. On the other hand, if you’re a data science professional, then you’d need to learn in detail about Numpy, Scipy, TensorFlow, Scikit-learn, Pandas, and several other libraries. At upGrad, we offer multiple programs to help you become an expert in this programming language and your desired tech field. If you want to become an expert in Python and use this robust language to solve business problems and drive your career, then we recommend checking out our Master of Science in Computer Science program we offer in partnership with Liverpool John Moores University. It’s an online degree course that lasts for 19 months and only requires a time commitment of 15 hours a week. The program teaches you the in-demand skills of the software development field and certifies you as an expert. More about the course:  The Master of Science in Computer Science program offers you 500+ learning hours and gives you the alumni status of Liverpool John Moores University and International Institute of Information Technology Bangalore. You’ll be joining a learner base of more than 40,000 students in over 85 countries across the globe. The program allows you to network globally and boost your professional growth. The MSc program offers six unique specializations: Full-stack development Blockchain development Big data Cloud computing DevOps Cyber Security If you have a non-tech background, you can join the Software Career Transition Bootcamp for non-tech & new coders. There’ll be fortnightly group mentorship sessions with industry mentors and 30+ projects and assignments, so you can test your knowledge and enhance your understanding of the concepts. Learn more about the course here: Master of Science in Computer Science. Conclusion Today we learned about the Python list append function. The append function allows you to add an item to the end of the list and is quite useful in many situations. We also learned how the append function is different from the extend function.  If you want to learn more about Python and become a tech professional, be sure to check out the course we shared above.
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by Rohit Sharma

16 Aug'21
List Comprehension in Python (With Examples)

6.62K+

List Comprehension in Python (With Examples)

Python is among the world’s most popular programming languages. In 2020, it ranked second in RedMonk’s ranking of programming language popularity. The reason behind its widespread popularity is its easy-to-understand code and simplicity. Writing code in python is quite simple if you’re familiar with the syntax. One of its unique highlights is its list comprehension feature. You can perform Python comprehension for lists by writing just one line of code!  The following points will illustrate what list comprehension is and how you can use it in different settings. We will also cover the differences present between list comprehension and for loops, which can be quite confusing. You’ll also learn about other related functions and how to use them:  What is list comprehension Python? Python offers multiple ways to create lists. One of the most effective ways among them is the list comprehension feature. It allows you to create lists by writing a single line of code.  You can use list comprehensions to create new lists from other iterable elements such as arrays, strings, tuples, lists, etc. It is made up of brackets with the expression. The system executes the expression for every element with the for loop to iterate over every element.  The syntax for list comprehension in Python is as follows: your_new_list = [expression for element in your_old_list if condition] Here, your_new_list is the new list (or the result). The expression depends on the variable you used for every element in your_old_list. Finally, the “if condition” is the filter. There are many reasons why Python developers prefer list comprehension over loops. The main reason is efficiency. You can create a list with far less effort and code when using list comprehension than you would while using loops As it takes fewer lines of code than loops, list comprehension also saves you a lot of time. It keeps the code simple and makes it more user-friendly. Moreover, list comprehension covers an iterative statement into a formula. If you want to gain more expertise on python, check out our data science programs from top universities. List comprehension Python examples We are sharing several examples of how you can use list comprehension in Python. It would be best to study them and replicate them in your own program after you have understood how they work. It would help you understand properly how effective of a tool list comprehension truly is: Example 1: In this example, we’ll create a simple list by using Python comprehension: Input: a = [i for i in range(5)] print a Output: [0, 1, 2, 3, 4] Example 2: In the example below, we’ll create a list with multiples of two: Input: new_list = [a*2 for a in range(10)] Output [0, 2, 4, 6, 8, 10, 12, 14, 16, 18] Example 3 You can multiply every item in a list by using list comprehension: Input old_list = [1, 2, 3] new_list = [item*2 for item in old_list] print new_list Output [2, 4, 6] Example 4 List comprehension isn’t limited to integers alone, you can also use it with strings. In this example, we’ll use list comprehension to create a list of the first letter of every word in our original list Input:  my_list = [“upgrad”, “is”, “fun”] result = [word[0] for word in my_list] print result Output [‘u’, ‘i’, ‘f’] Example 5 You can also extract numbers from a string by using list comprehension Input: old_list = “upGrad 123 is fun” new_list = [x for x in string if x.isdigit()] print new_list Output: [‘1’, ‘2’, ‘3’] Example 6:  You can also use list comprehension with functions, which are a vital part of mathematical implementations of Python: Input # first, we’ll create a function called triple def triple(x return x*3 # now you have a working function that prints a result if you enter a valid value >>> print triple(2) Output: 6 Now you can use list comprehension with this function to create more lists Input:  >>> [triple(x) for x in range(5)] print triple Output:  [0, 3, 6, 9, 12]   Difference between list comprehension and for loop A common way to iterate through a list is by using the for loop. However, list comprehension is a more efficient method to iterate through a list as it lets you perform the task with fewer lines of code.  Here’s an example to illustrate the difference. We’ll start with an empty list and modify it to make it a list of even numbers: Input # creating the empty list old_list = [] # using the for loop to create the new list for x in range(5): old_list.append(x*2) print old_list  Output:  [0, 2, 4, 6, 8] As you can see, the for loop requires you to use the append function to create the new list. You also had to create an empty list first so you can use the loop to modify the same. However, with list comprehension, you wouldn’t have to use another function as you can complete the task with a single line of code: Input:  # creating the set by using list comprehension old_list = [x*2 for x in range(5)] print old_list Output: [0, 2, 4, 6, 8] As list comprehension takes up less space and code, it also requires less computation power than using a for loop. This is beneficial while working on large programs as efficiency becomes a key issue when the code is substantially long. However, when you’re using list comprehension, you should avoid using ones that are excessively long in one line. Otherwise, the code wouldn’t remain user-friendly and it can be quite challenging to share your work with other developers. Keep in mind that you rewrite every list comprehension into a for loop but you can’t rewrite every for loop into a list comprehension. List comprehension is one of the many Python comprehension functionalities present in this programming language. Another comprehension functionality that’s highly popular is dictionary comprehension: What is dictionary comprehension in Python? Dictionary comprehension, as the name suggests, allows you to create dictionaries in Python. The syntax of a dictionary comprehension is: {k:v for (k,v) in iterable} Here, k stands for key and v stands for value. Let’s see it at work. In the following example, we’ll create two lists and use dictionary comprehension to generate a dictionary from them: Input: # using Python to showcase dictionary comprehension # creating two lists to represent keys and values keys = [1, 2, 3, 4, 5] values = [‘a’, ‘b’, ‘c’ ‘d’, ‘e’] # implementing dictionary comprehension new_dict = { k:v for (k,v) in zip(keys, values)} print new_dict Output: {1 : ‘a’, 2 : ‘b’, 3 : ‘c’, 4 : ‘d’. 5 : ‘e’} Dictionary comprehension makes it quite easy to create dictionaries in Python. However, you can also use list comprehension to generate a dictionary. In the following example, we’ll use list comprehension and create a dictionary: Input: new_dict = {x: x*2 for x in [5, 4, 3, 2, 1]} print new_dict Output: {5 : 10, 4 : 8, 3 : 6, 2 : 4, 1 : 2} Become a Python Expert List comprehension is one of the many functionalities present in Python. It is a highly versatile and useful programming language. Moreover, the syntax of Python is also very easy to understand and takes quite a little effort to get used to. Apart from these benefits, Python also offers numerous libraries to its users. It has a thriving community of developers and programmers who add new libraries to its collection regularly. The numerous libraries and functions available for Python make it useful in different sectors such as software development, data science, machine learning, and others. If you’re interested in learning Python, you should learn it in the context of the field you want to enter. Also, recruiters always look for certified professionals in this field because it assures them of the candidate’s expertise. Due to these reasons, it would be best to join a python course if you’re interested in pursuing a career with this skill. The International Institute of Information Technology Bangalore offers an Executive PG Program in Software Development with upGrad which is perfect for those who want to become experts in this programming language and pursue a tech career. The course will give you a well-structured way to study Python and other trending technologies to help you enter the industry as a job-ready professional. upGrad has over 40,000 paid learners in 85+ countries. Joining this program will also allow you to network internationally through upGrad’s vast learner base. The Executive PG Program in Software Development course is an online program that lasts for 13 months. It only requires a time commitment of 15 hours a week. The program offers six specializations to choose from Cybersecurity DevOps Cloud computing Big data Blockchain development Full-stack development  Along with these advantages, upGrad also offers 360-degree career assistance with this program so you can kickstart your career easily. You can learn more about the course here: Executive PG Program in Software Development. Conclusion You can try out list comprehension with simple lists at first and then move onto more complex applications of this functionality. List comprehension is an example of how flexible and robust Python programming is.  What do you think of list comprehension? How would you use it in your program?
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by Rohit Sharma

22 Aug'21