B.Sc. Data Science and Big Data Analytics (Hons)
Programme Overview
The MIT-WPU B.Sc. in Data Science and Big Data Analytics programme provides a purpose-built curriculum combining creativity, technology, mathematics, electronics, and statistics. As more industries are using data to make decisions, this programme includes subjects like predictive analytics, machine learning, natural language processing, and computer vision. These are required across technology, healthcare, finance, and marketing sectors, ensuring you are aligned with industry demands.
Experiential learning through industry projects and internships also forms an important part of the programme at MIT-WPU, enabling you to apply theoretical concepts in practice. The Big Data and AI components of the curriculum equip you with the knowledge and skills to develop predictive models and analytics tools to drive innovation. You will receive training in addressing the challenges of the modern data economy, with a particular focus on ethical data governance, privacy, and the creation of algorithms.
Programming languages such as Python, R, SQL, and Hadoop will all be at your disposal, providing you with an encyclopaedic supply of knowledge and tools to work with as you enter the field as a data analyst, machine learning engineer, and more. This will give you the best chance to excel in the competitive data science industry.
Major Tracks
- Data Science
- Big Data Analytics
- Machine Learning
Duration & Fees
Duration
4 Years
Applications Open for 2026
Fee Per Year
₹ 2,00,000
Scholarship
| Scholarship Name | MIT-WPU CET Score |
|---|---|
|
Dr. Vishwanath Karad Scholarship |
90 & Above |
|
MIT-WPU Scholarship I |
88 & Above |
|
MIT-WPU Scholarship II |
85 & Above |
Note: Best of JEE or MHT-CET Score will be considered for availing the scholarship.
Terms & Conditions Apply:
- All Scholarships are awarded on a First Come First Serve basis. All Scholarships are awarded as fee adjustments.
- To continue the scholarship for the entire duration of the programme, a minimum level of the academic score has to be maintained at an 8 CGPA across all semesters, attendance is to be maintained at a minimum of 80 percent and there should be no disciplinary action against the student.
For more detailed information visit our website: https://mitwpu.edu.in/scholarships
Eligibility
Minimum 50% aggregate score in 10+2/Class 12th or its equivalent examination in science stream with Mathematics subject (at least 45% marks, in case of Reserved Class category candidate belonging to Maharashtra State only)
OR
Minimum 55% aggregate score in any 3 years Engineering Diploma from State Government approved Institution or its equivalent.
Selection Process
The selection process for the Programme is based on MIT-WPU CET Entrance Examination 2025 & Personal Interaction (PI) score. Step 1) MIT-WPU CET UG Computer Science 2025 - Online proctored entrance exam and
Step 2) Personal Interview MIT-WPU CET UG Computer Science 2025 Exam Pattern:
Type of Questions: Objective
Number of Questions: 100
Marks: 100
Duration: 1 hr
Negative Marking: No
*Note: MIT-WPU retains the right to make changes to any published schedule. (The exact date and time of the online Examination and Personal Interaction will be communicated to the candidate once scheduled.)
Programme Highlights
- Exposure to International Perspectives and Industry : Through international academic collaborations and frequent interaction with industry, students are exposed to global trends and practices.
- Rigorous Curriculum : The curriculum is designed to balance fundamental topics with in-depth knowledge of data analytics and big data, preparing students for both higher studies and employment.
- Innovative Learning Environment : The use of the latest tools is necessary to enable an innovative learning environment.
- Cross-Disciplinary : Electronics, statistics, mathematics, and the principles of data science are essential knowledge that must be combined to become a better prediction analyst.
- Mentorship and Career Guidance : Faculty and career counsellors mentor and guide students through academic and career planning.
- Industry-Relevant Skills Training : Courses focus on specialised technological skills in industries such as AI, machine learning, and big data technologies, helping students become job-ready.
Programme Structure
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
I |
UC | Indian Constitution | 1 |
| I | UC | Environment and Sustainability | 1 |
| I | UC | Yoga - I | 1 |
| I | UC | Social Leadership Development Program | 1 |
| I | UC | Financial Literacy | 1 |
| I | PF | Computer Organization | 3 |
| I | PF | Database Management system | 4 |
| I | PF | C Programming | 5 |
| I | PF | Introduction to Data Science | 3 |
|
Total |
Credits: 20 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
II |
UC | Yoga - II | 1 |
| II | UC | Co-creation | 1 |
| II | UC | AI for everyone | 2 |
| II | UC | Foundation of Peace | 2 |
| II | UC | Indian Knowledge System (General) | 2 |
| II | UC | Sports | 1 |
| II | PF | Discrete Mathematics | 3 |
| II | PF | Data Structure using C | 4 |
| II | PF | Introduction to Statistical Analysis using Excel | 4 |
|
Total |
Credits: 20 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
III |
UC | Spiritual and Cultural Heritage: Indian Experience | 2 |
| III | UC | Research Innovation Design Entrepreneurship (RIDE) | 1 |
| III | UE | University Electives - I | 3 |
| III | PF | Advanced Statistics | 3 |
| III | PF | Python Programming | 4 |
| III | PM | Data Mining and Data Warehousing | 4 |
| III | PF | Business Analytics | 3 |
| III | PM | Data Visualization | 2 |
|
Total |
Credits: 22 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
IV |
UC | Rural Immersion | 1 |
| IV | UC | Life Transformation Skills | 1 |
| IV | UE | University Electives - II | 3 |
| IV | PM | R-Programming | 4 |
| IV | PF | Statistical Inference and Multivariate Analysis | 3 |
| IV | PF | Indian Knowledge System (Sci.& Tech) | 2 |
| IV | PM | Object Oriented Programming using Core Java | 4 |
| IV | PM | Introduction to Machine Learning | 4 |
|
Total |
Credits: 22 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
V |
UC | Managing Conflicts Peacefully: Tools and Techniques | 2 |
| V | UE | University Electives - III | 3 |
| V | PE | Program Elective - I | 4 |
| V | PM | Advanced Machine Learning | 5 |
| V | PM | Advanced SQL | 4 |
| V | Program Capstone | Mini Project-I | 3 |
| V | Program Capstone | Cognitive Skills | 1 |
|
Total |
Credits: 22 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
VI |
UC | National Academic Immersion Program | 2 |
| VI | PE | Program Elective - II | 4 |
| VI | PM | Data Engineering | 3 |
| VI | PM | Big Data Analytics | 4 |
| VI | PM | Financial Analytics | 4 |
| VI | Program Capstone | Mini Project-II | 5 |
|
Total |
Credits: 22 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
VII |
PE | Program Elective - III | 4 |
|
VII |
PM | Generative AI | 3 |
|
VII |
PM | Deep Learning | 4 |
|
VII |
PM | Research Methodology | 3 |
| Program Capstone | Research Paper Writing | 4 | |
|
Total |
Credits: 18 | ||
| Semester | Course Type | Course Name/Course Title | Credits |
|---|---|---|---|
|
VIII |
PE | Program Elective - IV | 4 |
|
VIII |
Program Capstone | Project / Seminar and Internships - Internship | 15 |
|
Total |
Credits: 19 | ||
| Semester | Course Type | Course Name/Course Title | Total Credits |
|---|---|---|---|
|
V |
Program Elective - I | Big Data Technologies | 4 |
|
V |
Program Elective - I | Cloud Computing for Big Data | 4 |
|
V |
Program Elective - I | Optimization Techniques for Data Science | 4 |
|
VI |
Program Elective - II | Natural Language Processing | 4 |
|
VI |
Program Elective - II | IoT and Sensor Data Analytics | 4 |
|
VI |
Program Elective - II | Time Series Analysis | 4 |
|
VII |
Program Elective - III | Data Security and Privacy | 4 |
|
VII |
Program Elective - III | Bioinformatics and Data Science | 4 |
|
VII |
Program Elective - III | Data Ethics and Governance | 4 |
|
VIII |
Program Elective - IV | Blockchain for Data Management | 4 |
|
VIII |
Program Elective - IV | Explainable AI | 4 |
|
VIII |
Program Elective - IV | MLOps (Machine Learning Operations) | 4 |
Career Prospects
Data Analyst
Data Scientist
Business Intelligence & (BI) Analyst
Machine Learning Engineer
Big Data Engineer
Database Administrator
Data Engineer
Quantitative Analyst (Quant)
Marketing Analyst
Healthcare Data Analyst
Consultant
Government Data Analyst
Academic Researcher
Supply Chain Analyst
Environmental Data Analyst
Social Media Analyst
Programme Outcomes
- Leverage computer science problem-solving abilities to build innovative solutions.
- Showcase analytical skills needed to build practical computer-based solutions.
- Write clean code and follow the best practices in ethical and industry standards
- Develop advanced professional skills to get success in Data Science & Big Data Analytics.
- Create a strong knowledge base for research and development in Data Science & Big Data Analytics, and Machine Learning; having a successful career in the field.
Placements & Recruiters
100% Placement Assistance
Top Recruiters
FAQs
The programme uses practical projects and advanced software tools to enrich the hands-on experience and approach towards successfully applying theory.
Students will learn about different platforms and programming languages, including those used in data science careers (Python, R, and SQL).
Graduates can work in multiple sectors like healthcare, finance, and technology as data analysts, machine learning engineers, etc.
Yes, the institute has a robust placement support system to ease the transition of students from the knowledge gained academically to industrial exposure.
For the B.Sc. Data Science programme, below is a list of independent salary ranges for various stages within the data science field. Graduate salaries for the Data Science programme at MIT-WPU :
2-4 years of experience as a Data Scientist
Compensation: ₹8L - ₹19L /yr
Senior Data Scientist (2-4 years experience)
Base Salary (India): ₹18L - ₹30L per year
Lead Data Scientist (5-7 years of experience)
Salary: ₹22L – ₹38L a year
Senior Data Scientist (6+ years of experience)
Salary range: ₹27L — ₹52L a year
Experience: 8+ years | Industry level: Director of Data Science
Salary Range: ₹14L – ₹68L per year
Such figures indicate the field’s lucrative potential and potential for growth — and they correspond with the programme’s aim to impart in-demand skills for today’s workforce.
Yes, it would be useful to get involved in data science-related clubs on your campus to gain more practical experience in addition to your education. Just a few of the many clubs :
Cosmos Astronomy Club : Anyone with an interest in astronomy and the scientific process can join, including novices.
Innovation Hub Club : The Innovation Hub is a space for learning and working where students can create innovative ideas and projects. There’s research, there’s innovation, there’s technology, and a creative learning environment.
To know more about clubs, click here: https://mitwpu.edu.in/life-wpu/clubs
MIT-WPU's Data Science and Big Data Analytics programme provides a balanced and comprehensive course of study with experiential learning in the most current technical fields like machine learning, predictive analytics, and computer vision. This programme opens up professional pathways across rapidly growing industry sectors like data science, AI, and cybersecurity. You’ll have access to real-world experience through internships, working on industry projects, and partnering with top companies, ensuring you’re in line with industry trends. The students at MIT-WPU get exposure to global opportunities through exchange programmes, research, etc. We train you to industry standards, both technically and ethically, so you can step confidently into the world of data analysis and big data.
- Mathematics and Statistics : Learn the math and statistics concepts involved in analysing data.
- Computer Science : Integrated programming languages and techniques for computational problem-solving.
- Database Management Systems : Learn how to store, organise, and retrieve large datasets efficiently.
- Machine Learning : Learn predictive analysis with algorithms and techniques to train machines.
- Artificial Intelligence : Gain insight into how intelligent systems are becoming common in domains where they can successfully complete tasks that previously required human intuition.
- Data Visualization : Learn to showcase data insights using graphs, charts, and interactive dashboards.
- Big Data Processing : This generally deals with processing and analysing large datasets using modern tools and technologies.
- Data Science Project : An in-depth, practical capstone project that solves real-life challenges.
admissions@mitwpu.edu.in
