| Degree | Bachelors |
| Full Form | Bachelor of Science in Data Science |
| Duration | 3 Years |
| Subjects Required | Physics, Chemistry, Mathematics |
| Minimum Percentage | Passing 10+2 with a minimum aggregate of 50% from a recognized board. |
| Average Fees | INR 60,000-5,00,000 Per Year |
| Average Salary | INR 3.5-7 LPA [Source: Glassdoor] |
| Employment Roles | Data Architect, Chief Executive Officer, Vice President, Business Operations Manager, Technical Product and Program Manager, Data Science Manager, Leading Manager, Analytics Manager |
Bachelor of Science in Data Science shortly known as BSc Data Science focuses on training the students with required knowledge and skills in data analytics, machine learning, and statistics to analyze real-world problems concerning big data using various tools, technology, mathematical modeling, and more.
BSc Data Science curriculum aims to develop skills in students to extract and analyze the given data to solve problems through data analysis. The students will also be trained in visualizing large sets of data and screening the relevant data required to solve the phenomena. BSc in Data Science graduates work in roles such as Business Analyst, Data Scientist, Data Analyst, Data Architect, Data Mining Expert etc. The average BSc Data Scientist’s salary ranges from INR 3.5-7 LPA.
Read More: How to Become a Data Scientist
The admission procedure for BSc Data Science course requires the candidate to fulfill a set of eligibility criteria such as merit score, subject requirement, age limit, etc. Listed below are the common eligibility criteria for the BSc Data Science course
BSc Data Science course is one of the most popular courses among students worldwide due to its demand, future scope, and career progression in the field of data science. Here are a few important pointers on why choosing a BSc Data Science course can be rewarding for students:

The admission into BSc Data Science course is done either through entrance examinations such as CUET, SET, NPAT etc or based on merit score of the previous qualifying examination in colleges such as Sathyabama Institute of Science and Technology, Coimbatore Institute of Technology, NMIMS Mumbai etc.
Listed below is the step-by-step admission process for B Sc Data Science courses:

B Sc Data Science Admission is based on the entrance exam score obtained by the candidate in entrance exams such as CUET, NPAT, SET, etc. Below listed are a few important entrance exams for BSc Data Science courses along with colleges accepting the entrance exam:
BSc in Data Science Entrance Exam | Application Date | Accepting Colleges |
| May 15 – May 24, 2024 (Closed) | Dr. A.P.J. Abdul Kalam Technical University, Amity University, Sharda University | |
| Jan 1 – May 25, 2024 (Closed) | NMIMS Mumbai, MIT World Peace University, LPU | |
| May 5- May 11, 2024 (Closed) | Symbiosis Centre for Management Studies Pune, Symbiosis Centre for Management Studies Hyderabad |
The annual BSc Data Science courses range from INR 60,000 to 5,00,000 per year. The B Sc in Data Science course is offered by private colleges such as Narsee Monjee Institute of Management Studies, Sri Ramachandra Institute of Higher Education and Research, etc., and government colleges such as IIT Madras, Maulana Abul Kalam Azad University of Technology, AMU, and more.
Below listed are the top colleges for B Sc Data Science in India along with their fee details
NIRF Ranking 2023 | Name of the College | Average Annual Fees |
1 | INR 2,27,000 | |
51 | INR 60,000 | |
57 | INR 2,25,000 | |
63 | INR 2,00,000 | |
88 | INR 3,60,000 | |
95 | INR 1,25,000 | |
100 | INR 1,30,000 | |
113 | INR 4,30,000 | |
151 | INR 75,000 | |
160 | INR 57,000 |

The BSc in Data Science is one of the popular and in-demand courses that can be pursued either full-time or through distance learning based on the candidate’s preference. Listed below are the BSc Data Science course details:
Types of BSc in Data Science | Eligibility Criteria | Duration |
Full-Time BSc Data Science | A minimum of 50% in 10+2 with PCM as a mainstream subject from a recognised board | 3 Years |
BSc Data Science Distance Education | A minimum of 50% in 10+2 with PCM as a mainstream subject from a recognised board | 3-5 Years |
BSc in Data Science Course is recognized by UGC-DEB and enables the student to pursue the course during their flexible time in a cost-effective way. Below are some of the important details about the BSc Data Science course
The first-year BSc Data Science syllabus covers topics such as Linear Algebra, Basic Statistics, Programming in C Lab, etc. and the second-year BSc Data Science syllabus covers subjects such as Data Warehousing and Multidimensional Modelling, Operation Research and Optimisation Techniques, Time Series Analysis, etc.
The third-year syllabus focuses on subjects such as Big Data Analytics, Data Visualization, Programming in Python Lab, etc. Listed below is the BSc Data Science subjects semester wise:
Semester I | Semester II |
English | Statistics for Data Science |
Programming in C | Probability Models for Data |
Mathematical Foundations for Data Science | Programming |
Data Science Fundamentals | Data Structures and Algorithm |
Foundations of Computer Science | Linear Algebra |
Environmental Science | Operations Research |
Elective | Elective |
Semester III | Semester IV |
Business Analytics | Machine Learning |
Data Management | Data Security and Privacy |
Python for Data Science | Data Wrangling with Python |
Data Analytics using R | Advanced Python for Data |
AI | Internet Technology |
Electives | Electives |
Semester V | Semester VI |
Big Data Analytics | R for Analytics |
Deep Learning | Techniques And Tools for Data Science |
Data Handling and Visualization | Elective |
Natural Language Processing | Internship |
Elective | Project |
Read More: BSc Data Science Syllabus and Subjects
The BSc in Data Science course is offered by top colleges with a key focus on equipping students with the skills required to extract, analyze, and visualize data using various technologies and tools. Below listed is the comparison of courses for the top 3 colleges offering BSc in Data Science course.
College Name | Symbiosis Skill and Open University | Sri Ramchandra Institute of Higher Education and Research | NMIMS Mumbai |
Annual Fees | INR 2,00,000 Per Year | INR 75,000 Per Year | INR 3,60,000 Per Year |
Admission Process | Candidates must have successfully completed 10+2 with 50% marks with specialisation in PCM as subjects | Candidates must have successfully completed 10+2 with 50% marks with specialisation in PCM as subjects | Candidates must have successfully completed 10+2 with 50% marks with specialisation in PCM as subjects |
Top Recruiters | Microsoft, Morgan Stanley, Samsung | Accenture, Apollo Munich, Cipla | IBM, Infosys, KPMG |
Average Placement | INR 13 LPA | INR 4.75 LPA | INR 26 LPA |
Bachelor of Computer Application courses focus majorly on computer science as subjects along with software applications using data science whereas the BSc Data Science course focuses less on software operations and more on developing algorithms that can identify patterns in data.
The table below showcases the differences between BSc in Data Science and BCA Data Science:
Course | BSc in Data Science | BCA Data Science |
Full Form | Bachelor of Science in Data Science | Bachelor of Computer Application in Data Science |
Course Overview | The course curriculum focuses on topics such as data visualisation, linear algebra, data mining, and more. | BCA curriculum focuses on subjects such as programming languages, statistics, computer fundamentals, data structures, and more. |
Stream | Science | Computer Science |
Duration | 3 Years | 3 Years |
Eligibility | Passing 10+2 with a minimum aggregate of 55% from a recognized board | Passing 10+2 with a minimum aggregate of 55% from a recognized board |
Entrance Exam | NPAT, CUET, SET | CUET, SET, IPU CET, MET, |
Top Colleges | LPU, Sharda University, PSG College of Technology | Symbiosis Institute of Computer Studies & Research, Loyola College,Christ University |
Annual Fees | INR 60,000 to 5,00,000 Per Year | INR 40,000 -3,00,000 Per Year |
Job Role | Data Analyst, Data Scientist, Research Analyst, Business Intelligence Analyst | Web Designer, System Manager, Software Developer, Computer Programmer, Web Developer, Software Developer |
Average Salary | INR 3.5-7 LPA | INR 3 LPA |
Read More: BCA Data Science
The average BSc Data Science Salary in India ranges from INR 3.5-7 LPA and the range can go up to INR 8 LPA with 3-5 years of work experience. Below listed are job roles for BSc in Data Science graduates along with their average entry-level salaries
BSc Data Science Jobs | Entry Level Salary | Salary After 3 Years of Experience |
Data Analyst | INR 4 LPA | INR 6-7 LPA |
Data Scientist | INR 3.6 LPA | INR 5-6.5 LPA |
Business Analyst | INR 4 LPA | INR 7 LPA |
Data Mining Engineer | INR 6.0 LPA | INR 6-8 LPA |
Research Analyst | INR 4.7 LPA | INR 6-7 LPA |
Read More: B.Sc Data Science Salary and Job Scope
After successful completion of the BSc Data Science course, students can opt for higher education to gain in-depth knowledge about data science, data analytics, and machine learning technologies for better career opportunities.
Listed below are some of the courses which can be pursued after B Sc Data Science
The career options in the field of data science are vast and the students will be employed in top MNCs such as Amazon, Meta, Microsoft, Capgemini, etc upon graduation. Below listed are a few career options after a BSc in Data Science along with job roles, descriptions, and hiring companies.
Job Role | Job Description | Hiring Companies |
Data Analyst | Focuses on activities such as data cleansing, data analysis, and reporting | Tata Consultancy Services, Accenture, Capgemini |
Business Analyst | Works on analyzing various business processes and implementing ways to improve them | Wipro, Genpact, Accenture |
Data Scientist | Analyze large data sets through statistical modeling, machine learning, etc., and extract valuable insights | IBM, Cognizant, Capgemini |
Data Architect | Focuses on three key pointers known as data strategy, data governance, and system design | L&T Tech, IBM, TCS |
Business Intelligence Analyst | Works on data aggregation, interactive dashboard development, and offering business insights | Oracle, Amazon, Dell |
B.Sc Data Science graduates are recruited by various private and government companies such as TCS, L&T Technologies, Accenture, IBM, RBI, etc. Listed below are a few recruiters for BSc Data Science graduates:
| Tata Consultancy Services | Accenture | Reserve Bank of India (RBI) |
| Infosys | Wipro | National Informatics Centre (NIC) |
| Oracle | SAP | Indian Council of Medical Research (ICMR) |
| Larsen & Toubro Technologies (L&T) | IBM | Indian Space Research Organisation (ISRO) |
| Capgemini | Cognizant | Bharat Electronics Limited (BEL) |
| Deloitte | HCL Technologies | Centre for Development of Advanced Computing (CDAC) |
| Intel | Qualcomm | Defense Research and Development Organisation (DRDO) |
Students who want to pursue BSc Data Science can get scholarships from private and government colleges or schemes based on merit score, annual income, and other related factors. Tabulated below are some of the scholarships for BSc in Data Science students:
BSc Data Science Scholarships | Benefits |
UpGrad Scholarship | Upto INR 50,000 |
INSOFE Big Data Scholarship | Upto INR 25,000 |
Manipal ProLearn Data Science Scholarship | INR 5,00,000 for one eligible candidate |
KVPY Scholarship | INR 28,000 Per Year |
Read More: BSc Scholarships
Below listed are the top 3 cities to pursue a BSc Data Science course based on top colleges, average living expense, top recruiters, and average starting salary:
Cities | Top Colleges Offering BSc Data Science Courses | Average Living Expense (INR) | Average Starting Salary (INR) | Top Recruiters |
| Delhi | Delhi University, Amity University | 15,000 – 25,000 | 3,50,000 – 5,00,000 LPA | TCS, HCLTech, Wipro, etc. |
| Hyderabad | Osmania University, Jawaharlal Nehru Technological University, GITAM | 15,000 – 20,000 | 4,00,000 – 5,00,000 LPA | Amazon, Deloitte, Accenture, etc. |
| Pune | Symbiosis International University, MIT World Peace University | 25,000 – 30,000 | 4,00,000 – 5,00,000 LPA | TCS, Capgemini, Infosys, Wipro, etc. |
To become a successful professional in the field of data science, candidates must sharpen both soft skills and technical skills. Below listed are some of the important skills required for BSc Data Science Graduates:
B.Sc Data Science subjects enhance students’ skills in data collection, analysis, interpretation and making data-driven decisions. This degree focuses on statistical methods, machine learning, data visualization, and programming. The B.Sc Data Science subjects are divided into core and elective courses, which are delineated in the sections below.
The core subjects under BSc Data Science equip students with foundational knowledge and skills critical for a comprehensive understanding of Data Science. The core BSc Data Science subjects generally provided across most top colleges include:
Elective subjects enable students to tailor their education based on personal interests, the potential for advanced study, and diverse career opportunities in the field of Data Science. The list of elective subjects under BSc Data Science includes:
BSc Data Science covers a range of subjects that develop skills to work with data and drive insights such as computer science and programming, machine learning, data visualization, text mining, data mining, etc. The important subjects covered in B.Sc Data Science syllabus are explored in detail in the following table:
BSc Data Science Subjects | Topics Covered |
Mathematics for Data Science | Matrices and Calculus, Sets and Foundations in Logic, Relations and Functions, Hypothesis Testing, Probability Theory, |
Programming in C | Programming Language, Problem-solving Techniques, Fundamentals of C, Functions, Arrays and Strings, Pointers, Structures, and Union, Introduction to Embedded C. |
Data Science Fundamentals | Data Analytics & EXCEL, Data Visualization, Data-driven Techniques, Advanced Data Analytics with Excel, Forecasting in Excel. |
Statistics for Data Science | Statistical Methods, Probability and Distribution, Correlation and Regression, Sampling and Testing, Statistical Inference. |
Python | Python Programming, File, Exception Handling and OOP, Numpy, Data Manipulation with Pandas, Data Cleaning Preparation and Visualization. |
Data Security and Privacy | Data Privacy, Static Data Anonymization, Privacy Preserving Data Mining, Synthetic Data Generation, Dynamic Data Protection and Privacy Regulation. |
B.Sc Data Science subjects 1st year focuses on foundational principles in data science while 2nd year delves into practical applications, and the 3rd year covers advanced topics and a hands-on project for specialized skill development. The BSc Data Science syllabus semester-wise is detailed below.
BSc Data Science 1st year program introduces students to the foundational principles of data science, covering topics such as statistics, programming, and data structure fundamentals. This first year BSc in Data Science syllabus is detailed in the table below:
Semester I | Semester II |
English | Statistics for Data Science |
Programming in C | Probability Models for Data |
Mathematical Foundations for Data Science | Programming |
Data Science Fundamentals | Data Structures and Algorithm |
Foundations of Computer Science | Linear Algebra |
Environmental Science | Operations Research |
Elective | Elective |
Practical Topics in First Year B.Sc Data Science Syllabus
The practical subjects taught in the B.Sc Data Science subjects 1st year are as follows
BSc Data Science second year syllabus explores subjects like business analytics, machine learning, and data management, gaining proficiency in Python and R. The practical labs enhance their technical skills. The second year BSc Data Science syllabus semester wise is given below:
Semester III | Semester IV |
Business Analytics | Machine Learning |
Data Management | Data Security and Privacy |
Python for Data Science | Data Wrangling with Python |
Data Analytics using R | Advanced Python for Data |
AI | Internet Technology |
Electives | Electives |
Practical Topics in Second Year B.Sc Data Science Syllabus
The second-year BSc in Data Science subjects for practicals are listed below:
The third year is dedicated to advanced topics in data science, including big data analytics, deep learning, and natural language processing. Students also work on a significant project that allows them to apply their knowledge. The third year BSc Data Science syllabus is listed in the table below:
Semester V | Semester VI |
Big Data Analytics | R for Analytics |
Deep Learning | Techniques And Tools for Data Science |
Data Handling and Visualization | Elective |
Natural Language Processing | Internship |
Elective | Project |
Practical Topics in Third Year B.Sc Data Science Syllabus
The third-year BSc in Data Science subjects for practicals are listed below:
The subjects and syllabus for BSc Data Science can differ across colleges, reflecting their unique curriculum and educational objectives. To access and download the BSc Data Science syllabus pdf, students should visit the official website of their selected university. Here’s a general outline of the syllabus of the top BSc Data Science colleges in India.
The BSc Data Science course at NMIMS delves into a comprehensive curriculum. It spans six semesters and equips students with a broad skill set to excel in the field of data science, culminating in a capstone project and research initiatives. The BSc Data Science syllabus semester-wise is provided in the tables below:
Semester I | Semester II |
Descriptive Statistics – I | Descriptive Statistics – II |
Introduction to Probability Theory | Probability Models for Discrete Data |
Univariate Calculus | Probability Models for Continuous Data |
Elementary Number Theory | Linear Algebra |
Discrete Mathematics | Numerical Methods |
Foundations of Computer Science | Introduction to Programming |
Introduction to R | Effective Communication |
Environmental Studies |
Semester III | Semester IV |
Statistical Inference for Data Science – I | Statistical Inference for Data Science – II |
Sampling Distributions & Applications | Regression Analysis |
Statistics Lab – I | Designs of Experiments |
Multivariate Calculus | Statistics Lab – II |
Mathematics Lab – I | Theory of Optimization & Graph Theory |
Data Management | Mathematics Lab – II |
Technology Lab – I | Machine Learning – I |
Data Analysis using Python | Technology Lab – II |
Research Writing | Data Wrangling with Python |
Research Initiative in Data Science – I | Research Ethics |
Research Initiative in Data Science – II |
Semester V | Semester VI |
Multivariate Analysis | Markov Chains |
Operations Research | Time Series & Forecasting |
Statistics Lab – III | Statistical Process Control |
Differential Equations | Statistics Lab – IV |
Mathematics Lab – III | Deep Learning Techniques |
Machine Learning – II | Technology Lab – IV |
Technology Lab – III | Data Visualization and Modelling |
Big Data Analytics | Entrepreneurship Skills |
Professional Skills | Capstone Project |
Research Initiative in Data Science – III |
Hindustan University’s BSc Data Science course explores topics like machine learning, data security, and big data analytics. B.Sc Data Science syllabus also provides flexibility with electives and a focus on real-world application through internships and projects. The semester-wise BSc Data Science syllabus semester wise is detailed below.
Semester I | Semester II |
English | Statistics for Data Science |
Mathematical Foundations for Data Science | Data Structure and Algorithm |
Programming in C | Operating Systems |
Data Science Fundamentals | Database Management System |
Computer Organization | Python for Data Science |
C Programming Lab | Database Management Lab |
Data Analysis with Excel Lab | Python Programming Lab |
Semester III | Semester IV |
Computer Networks | Machine Learning |
Artificial Intelligence | Data Security and Privacy |
Data Analytics using R | Professional Ethics and Life Skills |
Business Analytics | Data Handling and Visualization |
Elective: Time Series Analysis/Data Wrangling Techniques | Elective: Predictive Modelling and Analytics/Statistical Inference for Data Science |
Data Science Programming using R | Machine Learning Lab |
Business Analytics Lab | Data Handling and Visualization Lab |
Semester V | Semester VI |
Big Data and Analytics | Techniques and Tools for Data Science |
Principles of Deep Learning | Elective: Conditional Monitoring Techniques for Data Science/IoT Cloud and Data Analytics |
Elective: Social Network Analytics/Information Retrieval and Processing | Internship |
Elective: Computer Vision Techniques/Digital Image Processing using MATLAB | Project Work |
Big Data and Analytics Lab | |
Mini Project |
Projects are an integral tool of the BSc Data Science syllabus that bridges the gap between theory and practice. Listed below are some useful project topics for students to refer to:
The course structure for a BSc Data Science typically comprises a combination of core subjects, elective courses, and practical components. While specific courses may vary by university and field of study, a BSc course structure often follows a pattern:
The teaching methods and techniques in higher education such as B.Sc Data Science have evolved to engage and educate students effectively. A combination of traditional and modern approaches is often employed by BSc Data Science colleges in India. The methods include:
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