B.Sc. Data Science and Big Data Analytics

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
Duration
3 Years

Last Date to Apply : 09 June 2025
Programme Name

B.Sc. Data Science and Big Data Analytics

Fee Per Year

₹ 1,65,000




Highest CTC
INR 4.8 LPA

Scholarship
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.

Scholarship DetailsScholarship Details

*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.
Course Structure
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

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
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FAQ's

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.
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