B.Sc. Data Science and Big Data Analytics
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.
- Data Science
- Big Data Analytics
- Machine Learning
Last Date to Apply : 09 June 2025
B.Sc. Data Science and Big Data Analytics
| Scholarship Name | MIT-WPU CET Score |
| Dr. Vishwanath Karad Scholarship (100%) | 90 & Above |
| MIT-WPU Scholarship I (50%) | 88 & Above |
| MIT-WPU Scholarship II (25%) | 85 & Above |
Note: Student will be entitled to scholarship based on MIT-WPU CET 2025 CBT (Computer Based Test) Score.
*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
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.
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.)
- 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.
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
I |
University Core |
Effective Communication |
1 |
|
I |
University Core |
Critical Thinking |
1 |
|
I |
University Core |
Environment and Sustainability |
1 |
|
I |
University Core |
Foundations of Peace |
2 |
|
I |
University Core |
Yoga - I |
1 |
|
I |
University Core |
SLDP |
1 |
|
I |
Programme Foundation |
Computer Organisation |
3 |
|
I |
Programme Foundation |
Database Management System |
4 |
|
I |
Programme Foundation |
C Programmeming |
5 |
|
I |
Programme Foundation |
Introduction to Data Science |
3 |
|
|
Total |
22 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
II |
University Core |
Advanced Excel |
1 |
|
II |
University Core |
Financial Literacy |
1 |
|
II |
University Core |
Yoga - II |
1 |
|
II |
University Core |
Co-creation |
1 |
|
II |
University Core |
Indian Constituion |
1 |
|
II |
University Core |
IKS(General) |
2 |
|
II |
University Core |
Sports |
1 |
|
II |
Programme Foundation |
Discrete Mathematics |
3 |
|
II |
Programme Foundation |
Data Structure Using C |
4 |
|
II |
Programme Foundation |
Introduction to Cloud Computing |
3 |
|
II |
Programme Major |
Introdcution to Statistical Analytics using Excel |
4 |
|
|
Total |
22 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
III |
University Core |
Research Innovation Design Entrepreneurship (RIDE) |
1 |
|
III |
University Core |
Spiritual & Cultural Heritage; Indian Experience |
2 |
|
III |
University Electives |
UE - I |
3 |
|
III |
University Electives |
UE-II |
3 |
|
III |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - I |
1 |
|
III |
Programme Foundation |
Core Java |
4 |
|
III |
Programme Major |
Python Programmeming |
4 |
|
III |
Programme Major |
Data Mining and Data warehousing |
4 |
|
|
Total |
22 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
IV |
University Electives |
UE-III |
3 |
|
IV |
University Core |
Rural Immersion |
1 |
|
IV |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Project Based Learning - II |
1 |
|
IV |
University Core |
Life Transformation Skills |
1 |
|
IV |
Programme Foundation |
Linear Algebra and Calculus |
3 |
|
IV |
Programme Foundation |
IKS - 2 |
2 |
|
IV |
Programme Major |
Big Data Technologies using Hadoop |
4 |
|
IV |
Programme Major |
SPSS Programmeming |
3 |
|
IV |
Programme Major |
Stastistical Inference and Multivariate Analysis |
3 |
|
IV |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Lab on SPSS |
2 |
|
|
Total |
23 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
V |
University Core |
Managing Conflicts Peacefully: Tools and Techniques |
2 |
|
V |
Programme Capstone Project/ Problem Based Learning/ Seminar and Internships |
Project Based Learning - III |
1 |
|
V |
Programme Major |
R Programmeming |
4 |
|
V |
Programme Major |
Introduction to Machine Learning - I |
4 |
|
V |
Programme Major |
MOOC |
2 |
|
V |
Programme Capstone Project/ Problem Based Learning/ Seminar and Internships |
Research Paper Writing |
1 |
|
V |
Programme Capstone Project/ Problem Based Learning/ Seminar and Internships |
Data Analytics using python |
2 |
|
V |
Programme Electives |
|
4 |
|
|
Total |
20 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VI |
Programme Capstone Project/ Problem Based Learning/ Seminar and Internships |
Project Based Learning - IV |
1 |
|
VI |
University Core |
National Academic Immersion |
2 |
|
VI |
Programme Major |
No SQL |
4 |
|
VI |
Programme Major |
Introduction to Machine Learning -II |
4 |
|
VI |
Programme Capstone Project/ Problem Based Learning/ Seminar and Internships |
Mini Project - I |
4 |
|
VI |
Programme Electives |
|
4 |
|
|
Total |
19 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VII |
Programme Major |
Enterprernship Development |
3 |
|
VII |
Programme Major |
Data Visualization |
5 |
|
VII |
Programme Electives |
|
4 |
|
VII |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Mini Project - II |
4 |
|
|
Total |
16 |
|
| Semester | Course Type | Course Name/Course Title | Total Credits |
|
VIII |
Programme Electives |
|
4 |
|
VIII |
Programme Capstone Project/Problem Based Learning/Seminar and Internships |
Full Time Industry Internship |
15 |
|
|
Total |
19 |
|
- 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.
100% placement assistance
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.
You must qualify for the MIT-WPU CET Entrance Examination (not applicable for courses with Direct Admission schemes, i.e. PhD Admissions) and meet other requirements. After this, you will need to examine your skill level in data science.
Apart from the course curriculum, extracurricular clubs further promote data science, analytics, etc.
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 
