A recent study has highlighted that by 2026, the need for understanding big data and the skills of a Data Scientist will increase by 27.6%. As the data science course utilizes statistics and predictive analysis, the need for Data Scientists in the IT sector will rise. Hence, there will be greater job security and a good salary. Apart from these, the other major benefits of learning data science are:
More freedom and flexibility - Data science is a profile that offers freedom and flexibility in work. Data Scientists can work from anywhere, anytime, and at their convenience. Several organizations provide work flexibility considering the nature of the job of a Data Scientist.
Multidisciplinary tools - Data Scientists are trained to work with machine learning and deep technology to make sense of the collected data. They can also develop specific programs to suit their needs. This creative process and using the various tools make data science an interesting career option.
Constant growth guaranteed - Data science is an evolving field. The constantly changing demographic of data affects the job of a Data Scientist. This means that it is a practical field through and through. Another added advantage of this field is regular interactions with industry experts will be a learning experience.
Ideally, anyone who wants to know and work with big data can do a data science course. But, a specific specialization is required for data science dealing with numbers and programming tools. As mentioned above, data science is an interdisciplinary field that includes core subjects such as statistics, informatics, computer science, mathematics, domain knowledge, and machine learning. The data science courses are preferred by engineers and statisticians who are already well-endowed with computer and mathematical abilities.
Generally, to become a Data Scientist, it is necessary to have completed at least a bachelor’s degree in any of the following disciplines:
But, nowadays, you can pursue a career in data science even after passing class 12. You must have science and computer application as your core subjects in grade 12. Once you complete schooling, you can enroll in any undergraduate program offering data science as the core subject. If you have already finished college, you can opt for diploma or certification courses in data science. These are generally offered online.
Getting a data science certification is not difficult, provided you are diligent and serious about working as a Data Scientist. There are various options available for pursuing a career in data science. While some can opt for a bachelor of data science degree, and some can opt for an MS in data science. There are diploma courses too that can be pursued along with a job.
Data science can be opted as a subject at an undergraduate level, and the duration will depend on the level and the country; the time taken to complete a bachelor’s degree in three or four years. As an engineering subject, a data science course can take about four to five years.
A master's degree can last from one to two years, and an M Tech in data science course can also last two to three years. Data science is also available as a doctorate subject, and getting a Ph.D. in data science can help you research the topic or become a teacher at any coveted university. The duration will depend on the college and the thesis topic.
The part-time data science course is ideal for working professionals aspiring to balance work and studies. The duration of a part-time graduation degree is longer than that of a full-time course, as the credits and syllabus are covered in a longer-term. A dual advantage of opting for a PGDM course or a diploma is completing the course in 10 months and getting a quality education. The most popular part-time data science course is the Data Science Bootcamp.
The part-time course is offered online and covers the majority of the syllabus. Few institutions require students to visit the college or study centers to take tests or submit projects.
The one-year data science course is usually taught online and covers180 credits. The one-year program is divided into two semesters with live classes and a set number of assignments. A live assignment is provided at the end of the year to assess the student's learning progress.
Most professionals looking to advance their careers prefer an online data science course. With online data science courses, you can even apply to international universities and get ready to work with remote teams. IIT Madras offers an advanced online data science certification and artificial intelligence. With online classes, you work more on the practical aspect of the subject than just focus on the theory and principles of data science.
Classroom learning has always been preferred as it offers one-on-one sessions and a better in-person experience with teachers and peers. However, in the past few years, online classes and courses have not only made learning easy and convenient but help add skills to an existing career. Opting for a data science online course can also be a good choice if one has scored well and has relevant knowledge.
The key benefits of getting an online data science certification are:
Multiple options for courses and degrees
The variety of online courses is far greater than those available offline, data science being one of them. The curriculum of online courses covers all the basics for a specific specialization making the classes more engaging and subject-focused. You will fare better in your classes and tests when you learn what you love and are not limited to traditional learning methods.
Better opportunities for networking
The best part about online courses is that geographical boundaries are no longer a limiting factor. People living in different parts of the world and time zones can attend the same classes together and interact with each other on a cultural level. Another advantage of online teaching is access to top experts worldwide. Hence, the online model offers dual benefits to learners and teachers.
Better exposure to modern resources
You can use your computer and technology to gather maximum information from desired resources. When opting for online data science courses, you can access the latest and best resources and tools through a simple internet search. And the best part is that most of them are available for free. Accessing the required datasets and utilities at your convenience is easy with online tools and resources.
More cost-effective and convenient
The need for an institute, the associated electricity costs, and other study-related items would add to students' fees. With online classes, all these settings are not required, and students and working professionals can study as per their convenient time slots. Online courses are also budget-friendly, and you only pay for the classes you have attended or want to study.
In terms of convenience, online classes are more self-paced, and learners can join classes when they feel they can focus better. Most classes are recorded and uploaded on the educational portal, making them more accessible. Hence, online courses often have better results in comparison to offline classes.
The admission procedure for the data science course depends on factors like the duration and the number of classes and subjects you have chosen. The course level (undergraduate and postgraduate degrees) also determines the admission procedure for both online and offline courses.
The primary prerequisite for learning data science is prior knowledge of programming languages, especially Python, Perl, C/C++, SQL, and Java. Of these, Python is the most commonly used language for programming and developing apps. This is also a common coding language.
There is no age bar to pursuing a data science course. Many professional courses in the field are available on various online academic sites. But, to be eligible to start with data science, you need to have a background in science or mathematics and computer applications in senior secondary school. You can also have economics or commerce and computer applications to be eligible to pursue a data science course.
As data science is offered at undergraduate and postgraduate levels and also as a part-time or diploma course, the admission procedure for data science varies from college to college. Universities also determine the dates for examinations and interviews. Some universities give admissions based on high school performances. Some diplomas and certifications require no entrance examination ranks. But, you have to score high marks in your 12th board examination.
Data science courses can be pursued as an undergraduate course, a postgraduate course, or a PG diploma course for working professionals. All of these are available online.
The undergraduate level often requires students to sit for the Common Entrance Test or CET. Many universities require students to score well on this test before joining the classes. Some of the other bachelor’s degree entrance examinations are:
Sri Sri University conducts SSU CET for admissions to various programs in the university.
KR Mangalam Entrance Test includes admissions for Data Science.
AMET CET is conducted by the Academy of Maritime Education and Training University.
Jain University conducts an entrance test to shortlist students for its UG and PG Level programs.
The master’s or postgraduate course also requires students to appear for entrance examinations. There is another prerequisite for the student to be eligible. The student must have at least a 50% aggregate score in their Bachelor’s degree. Some of the entrance examinations conducted by several institutions are:
CUET is for students looking for admission to Christ University for a course in Data Science.
NIMSEE is a national-level entrance exam and is conducted offline. This exam is conducted by the NIMS University every year to grant admission.
CUCET is for admission to various courses offered by the various central universities of the country.
JNUEE is the entrance exam conducted by Jawaharlal Nehru University.
The field of data science is interdisciplinary; hence, universities and colleges have their own requirements for admission to the data science course. IIT Madras, for example, does not require students to appear in any entrance examinations for their data science courses.
The data science syllabus is vast and consists of interesting subjects. The main components of data science are Big Data, Machine Learning, Artificial Intelligence, and Modeling. While different colleges and universities offer various courses, the syllabus for beginners includes:
Introduction to Data Science
Understanding Exploratory Data Analysis
Model selection and evaluation
Storytelling with Data
Communication and Presentation
The advanced course includes the following:
Introduction to Data Science
Mathematical & Statistical Skills
Algorithms used in Machine Learning
Statistical Foundations for Data Science
Data Structures & Algorithms
Experimentation, Evaluation, and Project Deployment Tools
Predictive Analytics and Segmentation using Clustering
Applied Mathematics and Informatics
Exploratory Data Analysis
Business Acumen & Artificial Intelligence
Data science can be taken as a science discipline or engineering or technical discipline. The syllabus and the subjects vary as per the choice of the course. The common subjects of data science include:
Introduction and Importance of Data Science
Data Mining, Data Structures, and Data Manipulation
Algorithms used in Machine Learning
Data Scientist Roles and Responsibilities
Data Acquisition and Data Science Life Cycle
Deploying Recommender Systems on Real-World Data Sets
Experimentation, Evaluation, and Project Deployment Tools
Predictive Analytics and Segmentation using Clustering
Applied Mathematics and Informatics
Working on Data Mining, Data Structures, and Data Manipulation
Big Data Fundamentals and Hadoop Integration with R
Data Science in Machine Learning: Machine learning helps with the large-scale application of the theoretical models developed with data science's help. With a specialization in machine learning, Data Scientists can help develop new algorithms to help the models self-run.
Data Science in Data Mining: Data mining works as scouring through millions of data sets and extracting useful information. This is also a field where statistics plays a vital role. With a specialization in data mining, Data Scientists can incorporate predictive models and statistics to find patterns related to specific data sets.
Data Science in Quality Analysis: Applying data science in quality analysis positively impacts businesses and industries that rely on big data. Data Scientists can create models that rely on specific statistical data to extract analytical information that will help improve the quality of the business.
Data Science in Business Intelligence: Business intelligence is all about defining the future strategies of a company. This includes the profits, the current work pace, the conversion and generation of leads, and other crucial information in furthering the business. Data Scientists can develop algorithms that answer hypothetical questions and generate analytical reports.
Data science is a career option that can only evolve. Since data science deals with data and the current generation are all about sharing and collecting data, the need to have specific models in place will help keep the collected data in check. Artificial intelligence usually collects all the data that are streaming online. If a company implements particular reference points for filtering data, it will have to deal with only essential sets. This is what data science is all about. This field helps create those specific reference points with the help of algorithms and predictive models.
Today, data science finds its utilization in industries like aviation and healthcare. Cyber security relies on data science to create strong firewalls and filter messages and links. It is estimated that by 2023, the global data science market will generate $195.6 billion in revenue.
The steps that are involved in pursuing a data science course in India are simple. The pathways are broken down and explained in the following points:
Data science is a popular course in India. Many students and even professionals are opting to pursue a career in data science. The challenges that a Data Scientist faces act as the luring factor for these professionals. Also, the fact that diploma courses give them an equal opportunity to work at par with highly-paid professionals, all from the comfort of their homes, makes data science an attractive career choice. Now let us have a look at some major cities in India offering data science courses.
Mumbai is the financial capital of the country and the home of Bollywood. Many industries thrive in the city, and Mumbai has a lot to offer. The efficient contribution of the data scientists and engineers helps the smooth running of the backend processes for several industries and organizations. There are many colleges in Mumbai offering well-curated data science courses. Some of the top universities and colleges are:
Narsee Monjee Institute Of Management Studies - [NMIMS Deemed To Be University]
International School Of Engineering - [INSOFE]
IIT Bombay, Centre for Machine Intelligence and Data Science (C-MInDS)
SP Jain School Of Global Management -[SPJSGM]
MET Institute Of Software Development And Research - [METISDR]
Delhi is the capital of India and the political seat of power. Being home to the Indian Statistical Institute (ISI) and various prestigious colleges and universities, opting to study data science in Delhi can be a valuable decision. Some of the top colleges and universities are:
Indian Statistical Institute
Institute of Management Studies, IMS Ghaziabad
Amity University Online
Institute of Advanced Management and Research (IAMR)
Centre for Development of Advanced Computing (CDAC)
Tagged as the City of Joy, Kolkata is home to many prestigious universities and colleges. Considered to be one of India's top ten tech cities, Kolkata colleges offer data science as both science and technology disciplines. Some of the top colleges and universities for data science in Kolkata are:
Institute of Management Study, Kolkata
School of Computing and Analytics
NSHM Knowledge Campus
Chennai is popular for its art and culture, but the city is also known for its tech-savvy students. In fact, Chennai ranks fourth in the list of top ten tech cities in India. Some of the top universities and colleges offering courses in data science in Chennai are:
SRM Valliammai Engineering College
Indian Institute of Technology, IIT Madras
Academy of Maritime Education and Training, AMET Chennai
Chennai Institute of Technology
St. Joseph's College of Engineering
Being the country's tech hub, Bangalore has many tech spaces and IT hubs. Strong cyber security and data collection are essential for all these multinational corporations. Some of the top universities and colleges in Bangalore offering Data Science programs are:
Indian Institute of Science, IISc Bangalore
Indian Statistical Institute, Bangalore
International Institute of Information Technology, IIITB
M.V.J. College of Engineering
Jain Deemed-to-be University, Bangalore
Hyderabad is considered a data science and cyber analytical hub. The colleges and universities offering data science courses in Hyderabad are:
Gokaraju Rangaraju Institute of Engineering and Technology
ICFAI Business School (IBS), Hyderabad
Indian Institute of Technology, Hyderabad
IcfaiTech, IFHE Hyderabad
The city is known as the second IT hub in the country. Apart from the software and IT industries, Pune is also considered a major contributor to automotive manufacturing. Some of the known colleges and universities for a data science course in Pune are:
Symbiosis Centre for Information Technology, Symbiosis International, Pune
D.Y. Patil College of Engineering
MIT WPU - World Peace University, Pune
College of Engineering, Pune
Symbiosis Centre for Distance Learning, Pune
The former capital of Gujarat, Ahmedabad, is considered one of India's largest cities. This historical city located beside the Sabarmati river is known for its cotton textiles and diamond cutting techniques. But, the city is becoming a notable IT hub for the state. Some of the known data science courses in Ahmedabad are:
Ahmedabad Institute of Technology
Institute of Technology, Nirma University
While the field of data science has been around for over 40 years, data science as a study discipline is comparatively new, especially in India. The popularity of the field has made students keener to opt for online data science courses abroad. The chances for recruitment, job offers, placements, and campus learning are reasons students opt for online and offline data science courses abroad. Some of the benefits of pursuing data science from abroad are:
There are more syllabus variations, and students can curate the curriculum as per their interests and specialization requirements.
Colleges abroad offer pathway programs and foundation courses to bridge educational gaps. If computer science was not a subject in high school, students can take these pathway courses and then begin their data science course.
The placements are generally done along with the final semester, and often Fortune 500 companies hire students from campus.
Data science courses from abroad help get lucrative salary offers. Hence, they are highly sought after, especially in developing countries.
Some of the best and most affordable countries to consider when looking to study data science abroad are:
Denmark: Denmark is known for its beautiful weather and ranks among one of the happiest countries in the world. Danish universities focus on imparting quality education. The students gain practical and theoretical knowledge through the data science programs. Classes comprise small groups, so professors are attentive to each student. This further increases the students’ desire to learn better.
Germany: Known for its cutting edge and advanced technology, Germany incorporates practical learning and theoretical classes. This is known as ‘praxis’ and is the strength of German students. Industry experts teach the students directly, which is reflected in the professionalism of German students.
Norway: High-quality education and free tuition fees make Norway a sought-after destination for data science students. The free tuition fee offered by the state-funded private and public institutes makes up for the comparatively higher cost of living. The country’s focus on equality and quality education makes a strong student-teacher bond that aids in improving education.
Japan: Another technologically advanced country, Japan is a global hub for data science students. And, given that their machine learning and artificial intelligence technologies are very notable, there are numerous opportunities for data science students in various fields like robotics, marketing, and communication.
Data science is a lucrative career option, and India has seen a tremendous increase in data science jobs in the past few years. A recent example of the success of the data science domain in India is the use of data science applications in the healthcare sector during the COVID-19 phase. The collection and sorting of data, the filtering and pulling out of relevant data sets, especially those related to patient information, proved helpful to the concerned authorities.
Data is now the global currency and is an alluring field for students and companies. Organizations have realized the importance of data science for the success of their business. When data is properly analyzed, insights about customer preferences and trends can be correctly detected, and applying predictive models can generate future trends. In the entire process, data science plays a vital role.
Data scientists' tasks include collecting, analyzing, and interpreting the data sets that they have separated from the data lake. These difficult tasks can be simplified when the data scientist applies their specializations and utilize tools made for machine learning. This also helps the Data Scientist create deep learning algorithms that can be reused and tweaked to cater to other sets. This uncertainty about what data will be encountered and what trends can be predicted makes a career in data science attractive.
Data science is a very demanding field, and even freshers can draw a high annual salary package from top organizations after completing their degree from a reputable university. As data is essential for any business and industries worldwide that need actionable data to generate revenue, companies offer higher compensation to competent professionals. As a Data Scientist, you can limit yourself to becoming satisfied with the work details for a Data Scientist or opt for a more specialized profession that will also positively impact the salary. Data scientists' salaries depend on various factors.
For more information on data scientist salaries in India, visit our data scientist salary India page.
Getting a salary as a fresher abroad can compete with what mid-level Data Scientists earn from working in India. Being in the developing phase, India offers comparatively lower salaries than developed nations to data science professionals. However, there are instances that salaries in some professions have sky-rocketed in the past for Indian professionals. The option to work remotely for top companies across the globe makes it possible for people living in India to get lucrative salaries.
Some of the top-paying countries are:
United States of America
For more information on data scientist salaries abroad, visit our data scientist salary abroad page.
Average Salary Hike
Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well.
Solve a real industry problem through the concepts learnt in exploratory data analysis
Build a model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue
Help the sales team of your company identify which leads are worth pursuing through this classification case study
Apply the machine learning concepts learnt to help an international NGO cluster countries to determine their overall development and plan for lagging countries.
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them.
Build a machine learning model to identify fraudulent credit card transactions
Forecasting the sales on the time series data of a global store
In this assignment, you will work on a movies dataset using SQL to extract exciting insights.
In this assignment, you will apply your Hive and Hadoop learnings on an E-commerce company dataset.
This is an ETL project which will cover the topics like Apache Sqoop, Apache Spark and Apache Redshift
This assignment will test the learners understanding of the previous 2 modules on structured problem solving 1 and 2
With the IPL season commencing, let's go ahead and do an exciting assignment on sports analytics in Tableau.
Build a regularized regression model to understand the most important variables to predict the house prices in Australia.
Analyse the dataset of parking tickets
Practice MapReduce Programming on a Big Dataset.
In this module, you will solve an industry case study using optimisation techniques
This module will contain practice assignment & all resources related to a classification based problem statement.
The job of a Data Analyst is to make sense of the data that the Data Scientist has extracted. While both these disciples might seem interlinked or interchangeable, they are different. The specialization done by a Data Scientist is different from a Data Analyst. And a Data Scientist can also act as a Data Analyst if they have taken the required subjects during their classes.
Big data is a collection of structured, semistructured, and unstructured data collected in raw form and stored. These data are generally collected from places like the stock exchange market, social media platforms, etc. Analyzing these sets is not easy for traditional data analyzing software. Data mining relies primarily on big data, so correct analysis of the same is of utmost importance.
Yes, mathematics is a prerequisite for studying data science. Since data science involves statistical analysis based on predictive models, knowing linear programming and statistical mathematics is essential. If you did not have mathematics as a subject in high school, you could opt for pathway programs to bridge the educational gap.
Yes, data science is a part of bioinformatics, along with biology and computer science. Bioinformatics uses analytical tools to extract and analyze biological data, especially in genetics. For example, the Human Genome Project has recorded about three billion basic pairs of the human DNA system. This information will help researchers to understand mutations and genetically-linked diseases. Studies to prevent the same are also conducted based on these analytical data.
A postgraduate diploma in data science will help you further your career perspectives as data science is a versatile and broad area of specialization. If you have studied computer or mechanical engineering, you can opt for a part-time online degree in data science from one of these reputed colleges/ universities:
The process of structuring and analyzing unstructured data is done via coding. Proper knowledge of programming languages like C, C++, Java, SQL, or Python is another prerequisite for learning data science. When you know to code, you can make programs and algorithms to specify your needs and not spend hours manually scouring through the vast data sets.
Data science is an interdisciplinary subject, and hence, many topics are covered in this course. You can consider the following careers after successful completion of your data science course:
As data analytics is an essential part of data science, having a core specialization can help further your career and get a hike in your salary. Some of the certifications to consider are:
While data science is a technical subject, the job that entails the specialization of a Data Scientist also requires you to have certain soft skills or non-technical skills. These are necessary when you have to cater to large data. You need to be able to:
There is no such upper limit regarding age to study data science. This is a vast field, and many companies are constantly looking for competent Data Scientists. Statistics predict that the need for Data Scientists and other data-relevant fields will increase exponentially in the near future. And, there are not many people to fill up the roles. Hence, getting an additional degree or diploma in data science is beneficial.
Data science is a technical field, and having opted for science subjects and computer applications in high school is essential. Suppose you have not pursued computers or mathematics and statistics in your academic years. In that case, you need to show that you have taken those classes after school years to be considered eligible for studying data science.
Both MSc in data science and a postgraduate diploma (PGDM) in data science are courses that an individual undertakes after the completion of their undergraduate or bachelor’s degree. The core difference lies in the credits that these courses offer, the duration, and the specialization that students can opt for. The master’s degree is a full-time course with 180 credits. The PGDM is a part-time course with 120 credits. While both are specialization courses, the PGDM focuses on improving skill sets.
A Data Scientist creates questions through collected data, and a Data Analyst finds the solutions to those questions. Since both these fields are complementary to each other, there is no question of stating which is better over the other.
Yes, getting a Ph.D. in data science is possible even though you have opted for a postgraduate diploma course. You just need to clear the CSIR-UGC NET Exam.
Predictive analytics is a part of data science and data mining. With predictive analytics, you can teach the computer to go through the data history, track the patterns and the parameters that act in correlation and then predict an outcome. For example, if a power grid is shown to malfunction every time a particular sensor reaches a particular temperature. In that case, the machine will be taught to send notifications every time that sensor is at risk of reaching that particular temperature. This aspect plays a vital role in risk assessment and disaster aversion.
Programming language is the language that computers use to communicate with each other. Every student who studied computers in school has been taught DOS and C or C++. These languages, though older, are not very reliable when it comes to processing data. Hence, it is essential to polish the language skillset. Some of the best languages are:
The difficulty level of data science as a subject depends on the learner’s capability and the ability to grasp concepts. Being a technical domain, data science might seem to be a difficult subject on paper. Still, given the number of students enrolling in data science, it can be said that the subject is interesting. With practical knowledge along with theories, data science can be fairly easy to master.
Structured Query Language or SQL is a programming language that is used to retrieve and store data. Since data science is all about collecting and analyzing data, the retrieval and storage part is vital in generating historical datasets for the machine to upgrade itself.
Data science is primarily dependent on statistics and machine learning. Hence, proper knowledge about both these core components is essential. As a beginner, it is expected to know the following statistical disciplines:
Technically yes, data science can be self-taught, and people who have expertise in the domains of machine learning and programming languages can look up various videos and tutorials, and most of them are available for free. But, the certification is essential for getting a proper and well-paid job for companies would seek academically sound students over self-taught professionals.