SRM University Chennai
- Fees: ₹ 260000
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Degrees offered: B.E /B.Tech, M.Sc., B.Sc., BS, M.E /M.Tech.
Data Science is a fast-growing field that merges statistics, programming, and domain knowledge to extract insights from large datasets. In India, companies are rapidly investing in analytics, big data, and AI tools for smarter decision-making. This course prepares students to turn raw data into actionable knowledge for businesses and society.
To pursue a UG course in Data Science, students must complete their 10+2 education in the Science stream from a recognised board. For admission to PG programmes, candidates should hold a bachelor’s degree in a relevant field with at least 50 per cent marks from a recognised university or institute.
Data Science offers excellent career opportunities in India and abroad. Graduates work in areas like banking, healthcare, retail, and technology, using data to solve real business problems. With more companies investing in digital transformation, the need for skilled data professionals continues to increase across various industries.
Data Science courses provide students with in-depth knowledge of programming, statistics, and analytics to handle and interpret complex data. These courses prepare learners for careers in technology, business, and research sectors. Below are the key highlights of the Data Science course, including eligibility, duration, fees, top recruiters, and job profiles:
Particulars | Values |
---|---|
Branch Name | Data Science |
Top Courses | |
Duration | UG: 3-4 years PG: 2 years |
Admission Process | Entrance Exam or Merit-Based |
Entrance Examination | UG: JEE Mains, CUET UG, GUJCET, UPCET, MET PG: GATE, GITAM GAT, TS PGECET, SEE, TANCET |
Eligibility | UG: 10+2 with PCM and Entrance Exam PG: Bachelor's Degree in a relevant discipline with 50 per cent |
Fee Structure | Rs. 6,000 to Rs. 30.0 lakhs |
Career options | Data Science Manager, Data Science Consultant, Data Architect, and Data Scientist |
Salary Structure | Rs. 12 LPA |
Top Recruiters | Amazon, Deloitte, Flipkart, Accenture, IBM, Apple, Cisco and Google |
Data Science is a broad field within the domain of science, encompassing various topics such as Data Mining, Data Visualisation, Programming, Software Engineering, and Machine Learning Algorithms. Some of the degrees similar or related to Data Science are mentioned below:
B.Tech Computer Science and Data Science | BE Data Science Engineering |
B.Tech and M.Tech Data Science Integrated | BE Artificial Intelligence and Data Science |
Several reputed private colleges in India offer Data Science courses with modern facilities and industry-focused training. These institutes offer quality education, experienced faculty, and strong placement support, although their fees are typically higher than those of government colleges. Below are some top private Data Science colleges with their NIRF rankings and fee details.
Top Colleges | NIRF Ranking | Fees |
---|---|---|
11 | - | |
14 | Rs. 17 Lakhs | |
16 | Rs. 7.80 Lakhs | |
22 | - | |
Kalasalingam Academy of Research and Education, Virudhunagar | 33 | Rs. 4.51 Lakhs |
35 | Rs. 3.40 Lakhs | |
36 | Rs. 18.35 Lakhs | |
37 | Rs. 16.72 Lakhs | |
48 | Rs. 16 Lakhs | |
58 | Rs. 3.72 Lakhs |
Note: The above fee structure can be for any particular Data Science course (Diploma/ Degree/PGD).
Many government colleges in India offer Data Science courses at affordable fees while maintaining high academic standards. These institutions provide quality education, experienced faculty, and strong research opportunities. Below are some of India's top government Data Science colleges, along with their NIRF rankings and fee details.
Top Colleges | NIRF Ranking | Fees |
---|---|---|
1 | Rs. 62,500 | |
2 | Rs. 1.02 Lakhs | |
6 | Rs. 68,200 | |
8 | Rs. 1.11 Lakhs | |
12 | - | |
17 | Rs. 2.05 Lakhs | |
24 | Rs. 6.12 Lakhs | |
26 | Rs. 8.18 Lakhs | |
30 | Rs. 3.38 Lakhs | |
50 | Rs. 2.26 Lakhs |
Data Science courses are available at both undergraduate and postgraduate levels. The candidates should check the eligibility criteria before applying for admission. Students applying for a Data Science course should have an interest in Computers, Statistics, and Mathematics. Mentioned below are the general eligibility criteria at the undergraduate and postgraduate levels.
Students wanting to apply for undergraduate admission to a Data Science course should check the eligibility criteria of the desired institute before applying for the same. Most colleges accept students based on their scores in 10 + 2 examinations, while some colleges require students to appear for entrance exams.
To gain admission to top colleges, candidates should appear for the respective entrance examination conducted at the national, state, and university levels. Below, we have provided some of these Data Science entrance exams.
Exam Name | Exam Level | Conducting Body | Exam Schedule |
---|---|---|---|
National | NTA | ||
National | IITs | ||
National | NTA | ||
University | MAHE |
The eligibility criteria for the course can be checked on the official website of the institute or the programme brochure. While some universities require students to take entrance tests, others accept them based just on their scores in their bachelor’s degree.
Admission to PG courses in Data Science is done based on students’ scores in entrance exams like GATE, CUET PG, are others. Below, we have mentioned some of the top entrance exams:
Exam Name | Exam Level | Conducting Body | Exam Schedule |
---|---|---|---|
National | IITs | ||
National | NTA | ||
State | Anna University | ||
University | Sage University | - |
Data Science is a fast-growing field in India, with wide career prospects in industries like finance, healthcare, e-commerce, and technology. The Indian data science market is expected to reach around USD 2.55 billion (approx. Rs. 2.3 lakh crore) by 2033, growing at a CAGR of nearly 19 per cent. (Source: Coursera)
The need for skilled data professionals is rising sharply. IBM reports nearly 2.7 lakh new data-related jobs are expected by the end of 2024, reflecting a 28 per cent increase in demand. This shows the growing importance of data scientists who can analyse and interpret complex datasets to support business decisions. (Source: AnalytixLabs)
Minimum Fees | Maximum Fees | |||
---|---|---|---|---|
Private | Government | Private | Government | |
UG | ||||
PG | ||||
DOCTORAL | ||||
DIPLOMA |
The Data Science curriculum is designed to help students analyse and interpret data effectively to make informed decisions. It focuses on building strong analytical, programming, and visualisation skills through practical training and projects. Below are the detailed syllabi for both undergraduate and postgraduate Data Science courses.
For the UG syllabus, the Data Science course spans six semesters, covering programming, data analysis, statistics, AI, and software engineering. Students gain practical experience through projects, developing skills in Python, R, database management, and data visualisation. This syllabus is from Ganpat University.
First Year | |
Introduction To Programming I | Data Analysis-I |
Digital Electronics | Fundamentals of Mathematics |
Communication Skills | Web Designing –I |
Computer Maintenance And Troubleshooting | Principles Of Management In the Bhagavad Gita |
Introduction To Programming II | Data Analysis-II |
Information Technology | Effective Writing Skills |
Basic Statistics | Professional Ethics |
Web Designing-II | Microprocessor Programming |
Second Year | |
Data Structure | Advanced Database Management System |
Object-Oriented Concepts And Programming | Advance Statistics |
Introduction To Artificial Intelligence | Environmental Disaster Management |
Gui Programming | Web Designing-II |
Data Visualisation | Software Engineering |
Operation Research | Software Quality Assurance |
Third Year | |
Python Programming | Introduction To R Programming |
Data Mining | Linear Algebra And Probability Distribution |
Industrial Project – I | Professional Ethics And Life Skills |
Industrial Project – II | - |
For the PG syllabus, the Data Science course spans two years and covers core and elective subjects such as programming with R and Python, statistical analysis, machine learning, big data analytics, and AI applications. Students gain hands-on experience through labs, projects, and internships. This syllabus is from Uttaranchal University.
First Year | |
Mathematical Methods For Data Science | Data Science & Statistical Analysis |
Database Management System | Programming With R & Python |
Research Methodology & Ethics | Programming With R & Python Lab |
Data Analytics Algorithm | Big Data Analytics |
Matlab Programming | Data Visualisation |
Latex & Word Processing | Matlab Programming Lab |
Second Year | |
Data Warehouse And Data Mining | Modeling & Simulation |
Multivariate Techniques For Data Science | Business Analytics |
Machine Learning | Minor Project/Internship |
Business Analytics Lab | Machine Learning Lab |
Artificial Intelligence & IoT | Marketing Analytics And Operations Research |
Deep Learning | Social Media & Network Analytics |
Major Project | Artificial Intelligence & IoT Lab |
Deep Learning Lab | - |
After completing Data Science courses, graduates can find opportunities in research labs, educational institutions, multinational companies, tech firms, and consulting organisations. They can apply their analytical and technical skills across industries to solve real-world problems. Some of the popular job roles in this field are listed below:
Job Profiles | Description |
---|---|
Data Scientists are professionals whose role is to perform research activities and provide suggestions for improvement in various parts of a business organisation. They analyse large amounts of information to discover trends and patterns and build predictive models and machine-learning algorithms. | |
Data Engineers are professionals who are in charge of planning, constructing, and maintaining the infrastructure that allows for data storage, processing, and retrieval. They deal with big data sets to build data pipelines that transport data from source systems to data warehouses. | |
Data Analysts are professionals whose work includes collecting and analysing data to identify trends, insights, and solutions. They require knowledge in various fields such as Maths, Economics, Statistics, and Computer Science. | |
Business Analysts are professionals who analyse a company’s existing products, services, and systems. They identify issues in virtually any part of the organisation, including IT processes, organisation structures, or staff development. |
Data Science continues to grow rapidly, with global demand for skilled professionals increasing each year. Organisations are adopting advanced analytics, AI, and machine learning for better decision-making. Alongside current opportunities, the field is expected to evolve further, creating new roles and specialisations. Some of the current and upcoming trends in Data Science include:
Data Science graduates can work in finance, marketing, banking, IT, healthcare, and e-commerce, applying analytical skills to solve business problems and improve decisions. Demand for skilled data professionals is growing rapidly. Below are some top recruiters.
The average salary after a Data Science course depends on many factors such as the job profile, experience and skills of the candidate, and the location of the company. Below is a table showing the average salary per annum offered in different job roles in the field of data science:
Job Profiles | Average Salary (LPA) |
---|---|
Data Scientist | Rs. 15.1 LPA |
Data Engineer | Rs. 11.6 LPA |
Data Analyst | Rs. 6.7 LPA |
Business Analyst | Rs. 9.8 LPA |
Source: AmbitionBox
To excel in a Data Science career, students must have a mix of technical and analytical abilities, along with problem-solving aptitude. Some of the essential skills required in this field are:
The Data Science curriculum prepares students with the skills and knowledge needed to manage, analyse, and interpret large datasets. It focuses on techniques, tools, and methods essential for handling data efficiently in business, technology, and research environments.
Students study subjects like statistics, programming, algorithms, and machine learning, gaining practical skills to generate insights, solve complex problems, and support data-driven decision-making in organisations.
Answer :
The role of a Data Scientist is in high demand and is projected to grow as businesses and organisations continue to gather and analyse large volumes of data for insights and informed decision-making. Industries such as Finance, Marketing, Banking, and IT need experts who can handle, analyse, and derive valuable solutions from data.
Answer :
Generally, for an undergraduate course, the candidates need to clear the 10+2 in PCM with a valid score. For a postgraduate course, candidates are required to have a Bachelor's degree in Data Science or a related discipline with a valid aggregate mark as specified by the desired institute.
Answer :
Students can gain admission to Data Science courses by qualifying in various entrance exams, including CUET UG, JEE Main, JEE Advanced, and GATE.
Answer :
UG courses are generally of three to four years duration, whereas PG courses are of two years.
Answer :
Data science deals with questions to be asked in business by analysing various data and providing much broader insights. On the other hand, data analytics is about finding the answers to the questions. Data science professionals use programming languages such as Python, and JAVA. while data analytics professionals use programming languages such as SQL, and SAS.
Answer :
Making a career in this field is a good career option for students as there is a wide range of job opportunities available all around the globe. It is the only way for businesses all over the world to get results or insights into their operations and also get suggestions for making important business decisions.
Answer :
Top engineering institutes in India providing specialisation in Data Science are IIT Madras, IIT Delhi, VIT Vellore, NIT Surathkal, and BITS Pilani.
Answer :
Some of the top job roles in Data Science include Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, Data Architect, Business Analyst, and AI Specialist.
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