B.Sc. (Major: Data Science)
Education goes beyond textbooks and classrooms. We believe in empowering students to explore their passions challenge conventions.
The Bachelor of Science (B.Sc.) Major in Data Science is an innovative undergraduate program designed to prepare students for the rapidly growing field of data-driven decision-making. This program integrates core concepts from mathematics, statistics, and computer science with modern data analysis techniques to help students understand, interpret, and extract meaningful insights from complex datasets.Students gain practical experience in programming languages such as Python and R, data visualization, database management, and machine learning. The curriculum focuses on both theoretical foundations and hands-on applications, enabling students to work with real-world data and solve practical problems across various industries.The program develops essential skills in analytical thinking, problem-solving, statistical reasoning, and technical computing. Graduates are well-prepared for careers in data science, analytics, information technology, finance, healthcare, and business intelligence, as well as for advanced studies in Data Science, Artificial Intelligence, Statistics, or related fields.
Program Highlight
B.Sc. (Major: Data Science)
Typical Program Structure
- Course Bachelor of Science (B. Sc. (Major: Data Science)
- Duration: 3 Years (6 Semesters)/ 4 Years (8 Semesters)
- Mode: Full-time undergraduate program
- Eligibility: 12th pass (Science stream with mathematics as one of the subjects) from a recognized board
Objectives of the Program
The primary objective of this program is to provide a foundation of computing principles for effectively using information systems and enterprise software.
It helps students analyze the requirements for system programming and exposes students to information systems
This programme provides students with options to specialize in various software systems.
To produce outstanding Computer Scientists who can apply the theoretical knowledge into practice in the real world and develop standalone live projects themselves
To provide an opportunity for the study of modern methods of information processing and its applications.
To develop among students the programming techniques and the problem-solving skills through programming
To prepare students who wish to go on to further studies in computer science and related subjects.
To acquaint students with working effectively with a range of current, standard Office Productivity software applications.
Programme Specific Outcomes (PSOs)
Discipline knowledge
Acquiring knowledge on the basics of Computer Science and the ability to apply design principles in the development of solutions for problems of varying complexity.
Problem Solving
Improved reasoning with strong mathematical ability to identify, formulate, and analyze problems related to computer science, and exhibiting a sound knowledge of data structures and algorithms.
Design and Development of Solutions
Ability to design and develop algorithmic solutions to real-world problems.
Programming a computer
Exhibiting strong skills required to program a computer for various issues and problems of day-to-day scientific applications.
Application Systems Knowledge
Possessing a minimum knowledge to practice existing computer application software.
Communication
Must have a reasonably good knowledge of communication, both oral and written.
Ethics on Profession, Environment and Society
Exhibiting professional ethics to maintain the integrity in a working environment and have concern for societal impacts due to computer- based solutions for problems.
Lifelong Learning
Should become an independent learner. So, learn to learn ability
Motivation to take up Higher Studies
Inspiration to continue education towards advanced studies in Computer Science.
| Regular Students | Required Credits |
|---|---|
| Core Courses | 36 Credits |
| Data Science Major Courses | 45 Credits |
| Elective Courses | 12 Credits |
| Project / Internship | 9 Credits |
| Total | 120 Credits |
Core Courses
The Science (S) Core develops a strong foundation in scientific principles, analytical thinking, and evidence-based problem-solving These courses introduce students to the fundamental concepts of the natural world while strengthening their abilities to observe, experiment.
| Semester 1 | Courses Code | Core Courses | Credits |
|---|---|---|---|
| Foundations in Communication & Critical Thinking (12 Required Credits) | IBS301 | International Business Management | 3 Credits |
| BUS109 | Introduction to Microeconomics | 3 Credits | |
| MKT200B | Principles of Marketing | 3 Credits | |
| BUS308B | Strategic Management | 3 Credits | |
| Accounting | BUS325B | Introduction to Operations Management & Decision Science | 3 Credits |
| FIN305 | Introduction to Corporate Finance | 3 Credits | |
| BUS110 | Introduction to Macroeconomics | 3 Credits | |
| ACC101 | Introduction to Accounting | 3 Credits | |
| Management | BUS100A | Introduction to Business | 3 Credits |
| BUS211C | People and Organization | 3 Credits |
Science (S) Core
The Science (S) Core develops a strong foundation in scientific principles, analytical thinking, and evidence-based problem-solving These courses introduce students to the fundamental concepts of the natural world while strengthening their abilities to observe, experiment.
| Semester 2 | Courses Code | Science | Credits |
|---|---|---|---|
| Science | PHY 101 | Conceptual Physics | 3 Credits |
| BIO 105 | Introduction to Life Sciences | 3 Credits | |
| PHY 101 | Introduction to Physical Science | 3 Credits | |
| ENV 110 | Environmental Science | 3 Credits | |
| Technology | CS 101 | Digital Foundations and Applied Programming | 3 Credits |
| TECH 205 | Management Information Systems (MIS) | 3 Credits | |
| ENGR 100 | Introduction to Engineering Principles | 3 Credits | |
| DATA 210 | Data Management and Visualization | 3 Credits | |
| Mathematics | MATH 115 | College Algebra and Trigonometry | 3 Credits |
| STAT 201 | Probability and Statistics | 3 Credits |
Business (B) Core
The Business Core, requiring 30 credits (typically eleven 3-credit courses), is the largest component of the foundational curriculum. It ensures students gain a comprehensive, interdisciplinary understanding of the functional areas necessary to operate and manage an organization.
| Semester 3 | Courses Code | Business Core | Credits |
|---|---|---|---|
| Finance | IBS301 | International Business Management | 3 Credits |
| BUS109 | Introduction to Microeconomics | 3 Credits | |
| MKT200B | Principles of Marketing | 3 Credits | |
| BUS308B | Strategic Management | 3 Credits | |
| Accounting | BUS325B | Introduction to Operations Management & Decision Science | 3 Credits |
| FIN305 | Introduction to Corporate Finance | 3 Credits | |
| BUS110 | Introduction to Macroeconomics | 3 Credits | |
| ACC101 | Introduction to Accounting | 3 Credits | |
| Management | BUS100A | Introduction to Business | 3 Credits |
| BUS211C | People and Organization | 3 Credits |
Dr Liladhar Rewatkar
M. Sc. (CS), M. Phil. (CS), Ph.D.
Head, Senior Assistant Professor (Grade 11)
Dr Debasis Das
MCA, M. Sc., MBA, Ph. D.
Assistant Professor
Dr Avinash Hedaoo
M. Sc. (CS), Ph. D. SET
Assistant Professor
Dr Vijay Nikam
MCA, Ph. D.
Assistant Professor
Mr. Chandrashekhar Tople
M.Sc. [CS], SET, B. Ed
Assistant Professor
Ms. Priyanka Chandawar
MCA, NET
Assistant Professor
Ms. Poorva Wagh
MCA, M. Sc. NET
Assistant Professor
Ms. Sharvari Ramteke
M. Sc. (CS) NET
Assistant Professor
Mr. Ajay Nanwatkar
MCA,SET
Assistant Professor
Ms. Neha Samundre
MCM, M. Sc.
Assistant Professor
Ms. Rupali Surve
M. Sc. (CS) M.Phil. B. Ed.
Assistant Professor
Ms. Rajshree K. Akare
MCA
Assistant Professor
Ms. Mrunali A.Nikure
M. Sc. (CS)
Assistant Professor
Ms. Anamika Bhagat
M. Sc. (CS), SET
Assistant Professor
Ms. Nancy Purohit
M. Sc. (CS), MGSC
Assistant Professor
Ms. Shikha Gajbhiye
M. Sc. (Maths)
Assistant Professor
Ms Naina Khokad
MCA
Assistant Professor
Ms. Harshita Nagpure
M. Sc. (CS)
Assistant Professor
Ms. Sneha Ambekar
MCA
Assistant Professor
Ms. Nayana Puri
B. E.
Assistant Professor
Ms. Jyoti Yadav
M. Sc. (Stats)
Assistant Professor
Ms. Mansi Dhenge
MCA
Assistant Professor
Ms. Gitanjali Kale
M. Sc. (CS)
Assistant Professor
Publication
| Sr.No. | Year | Title of Papers | DOI |
|---|---|---|---|
|
1 |
2025 |
Rewatkar L & Awasare P. ‘Customer Churn Prediction from Large Datasets in Python’, STAP Journal, Vol. 11(3), 2025, pp.300-305. |
https://doi.org/24.20089.STAPS.2025.V11.3.01630 |
|
2 |
2025 |
Rewatkar L & Choudhary S. ‘Predicting Disease Outbreak from Healthcare Data Using Python’, STAP Journal, Vol. 11(3), 2025, pp.306-313. |
https://doi.org/24.20089.STAPS.2025.V11.3.01631 |
|
3 |
2025 |
Rewatkar L & Gaikwad S. ‘Customer Purchase Pattern Analysis in Retail Using Power BI’, STAP Journal, Vol. 11(3), 2025, pp.314-322. |
https://doi.org/24.20089.STAPS.2025.V11.3.01632 |
|
4 |
2025 |
Rewatkar L & Rokde S. ‘Visualizing an Interactive Sentiment Analysis Dashboard for Social Media Data with Python’, STAP Journal, Vol. 11(3), 2025, pp.323-329. |
https://doi.org/24.20089.STAPS.2025.V11.3.01633 |
|
5 |
2025 |
Rewatkar L & Khadatkar T. ‘Cloud-based Data Lake Implementation Using Python’, STAP Journal, Vol. 11(3), 2025, pp.330-337 |
https://doi.org/24.20089.STAPS.2025.V11.3.01634 |
| Sr.No | Faculty Name | Books Titles | National / International | ISBN | Publisher |
|---|---|---|---|---|---|
|
1 |
Dr Liladhar Rewatkar, Dr Nirzar Kulkarni, Dr Ujwal Lanjewar & Dr Manjiri Pathak |
Computer Application in Business |
National |
978-93-91322-82-3 |
Alliance & Co., Nagpur |
|
2 |
Dr Liladhar Rewatkar, Dr Nirzar Kulkarni, Dr Ujwal Lanjewar & Dr Manjiri Pathak |
Content Writing |
National |
978-93-91322-90-8 |
Alliance & Co., Nagpur |
|
3 |
Dr Liladhar Rewatkar, Dr Ujwal Lanjewar & Dr Nirzar Kulkarni |
Internet of Things |
National |
978-93-91322-83-0 |
Alliance & Co., Nagpur |
|
4 |
Dr Liladhar Rewatkar, Dr Ujwal Lanjewar & Dr Mahendra Dhore |
Basics of Python |
National |
978-93-91322-83-0 |
Alliance & Co., Nagpur |
|
5 |
Dr Liladhar Rewatkar, Dr Ujwal Lanjewar & Dr Jageshwar Keche |
Desktop Publishing |
National |
978-93-91322-92-2 |
Alliance & Co., Nagpur |
- Name of the Inventor :Dr Liladhar Rewatkar
- Patent Journal Publication Date :3rd June 2022
- Application No. :202221028424 A
- Title of the Invention :Systematic Approach to improve bug life cycle using agile methodology for quality software
- Patent Status : Published
- Name of the Inventor : Dr Liladhar Rewatkar
- Patent Journal Publication Date :9th February 2023
- Application No. :202441033647 A
- Title of the Invention :An e-Authentication system based on Artificial Intelligence, Big Data, and cybersecurity using QR codes and OTPs.
- Patent Status : Published
About Programs Fees
The cost of the program at Prerna College includes tuition fees, examination fees, and other academic charges as prescribed by the institution and affiliated university.
Tuition Fees: Competitive and student-friendly fee structure
Examination & Enrollment Fees: As per RTM Nagpur University norms
Additional Charges: Laboratory, library, and extracurricular activities
| Spring 2025 | Summer 2025 | Fall 2025 | Winter 2025 | Annual | |
|---|---|---|---|---|---|
| 17 weeks | 6 weeks Summer 1 3 Weeks Summer 2 3 Weeks | 16 weeks | 17 weeks Winter 1 3 Weeks Winter 2 3 Weeks | Costs USD | |
| Enrollment Fee (Onetime fee) | $560 | $560* | $660 | ||
| Orientations Fee (Onetime fee) | $159 | $159* | $159 | ||
| Medical Insurance (Yearly) | $68 | $68 | |||
| Tuition | $4,129 | $1,139 | $5,138 | $1,028 | $11,434 |
| Residence | $728 | $364 | $728 | $364 | $2,184 |
| Breakfast Fee | $448 | Not offered | $448 | Not offered | $896 |
| Activity Fee | $100 | $100 | $200 | ||
| Total Fast Year | $6,192 | $1,503 | $7,133 | $1,392 | $16,220 |
| Total Second Year | $5,192 | $1,503 | $7,133 | $1,392 | $15,220 |
Apply Now
Take the first step toward a successful career in Data Science by applying to our B.Sc. Major in Data Science program. Our admission process is simple, transparent, and student-friendly.Interested candidates can apply online by submitting the completed application form along with academic transcripts and required documents. Early application is recommended to secure your admission.Join a program that combines academic excellence, practical experience, and industry-relevant skills to prepare you for the future of data-driven decision making.
Start your journey today and become a skilled Data Science professional.
Admissions Requirements
Document Required
- Completed application form
- HSC/12th mark sheet and passing certificate
- SSC/10th mark sheet and passing certificate
- School leaving certificate
- Recent passport-sized photographs
- Caste certificate/category Certificate as per Maharashtra norms (if applicable
- Valid ID proof