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Work-Linked M.Sc Data Science

Study, Work and Earn Together at the Same Time

*Special Fee Applicable for CU Alumni Students
Course Eligibility:

Course Eligibility:

Candidate must have completed bachelor's degree in B.A. / BCA / B.Sc. (Statistics or Mathematics or Computer Science) / B.E. / B.Tech.

Internship Eligibility:

Age limit: 26 years

*Earnings depend on role, industry, company policies, and internship availability.

Course Fees:

Stipend

Earn up to ₹4.0 Lakhs/year with the internship of your choice*


What are Work-Linked Degrees?

Our work-integrated degree program lets you gain practical work experience through internships, while completing your degree with Chandigarh University.



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Program Overview :

The M.Sc. Data Science Work-Linked Program is designed to equip students with the essential skills needed to excel in the rapidly growing field of data science. This program combines rigorous academic coursework with valuable industry experience, allowing students to learn advanced data analysis, machine learning, and statistical techniques while simultaneously applying their knowledge in real-world business environments.

By participating in this work-linked model, students gain hands-on experience with data-driven decision-making processes, solving complex problems, and using cutting-edge technologies like Python, R, and big data platforms. The program is structured to ensure that students develop the technical expertise and analytical mindset required to tackle challenges across industries such as finance, healthcare, and technology.

Education Highlights

UGC-Recognised Degree

Work on Live Data Projects During the Program

Learn Python, R, SQL, and Machine Learning Tools

Hands-On Training with Real Business Data

Earn a Stipend While Gaining Experience

Mentorship from Data Experts and Academic Faculty

Program Structure


Subjects Credits
SQL Programming 4
Advanced Database Management Systems 4
Communication and Soft Skills 3
Python Programming 4
Applied Probability and Statistics 4
Total Credit 19
Subjects Credits
Calculus and Linear Algebra for Data Scientists 4
Deep Learning 4
Data Analysis and Visualization 4
Machine Learning 4
Advanced Machine Learning 4
Total Credit 20
Subjects Credits
Web Technologies 4
Optimization 4
Java Programming 3
Data Structures and Algorithms 5
Cloud Native Development 4
Minor Project (Software Dev) 2
Total Credit 22
Subjects Credits
Natural Language Processing 4
Data Engineering 4
Data Mining and Warehousing 4
Applied Business Analytics 4
Major Project 4
Total Credit 20

Course Fee


Admission Fee: INR 1,000

Course Fee (Per Semester): INR 36,667 INR 27,500

25% Early Bird Discount on Program Fee


Master of Science (Data Science) SEM I
SEM II
SEM III
SEM IV
Course Fee (Discounted) 27,500 27,500 27,500 27,500
INR 1,46,668 After Early Bird Discount INR 1,10,000

Learning Outcomes

Clean and Process Real-World Datasets

Build Basic Predictive Models

Create Dashboards and Visual Reports

Perform Exploratory Data Analysis (EDA)

Work with Tools like Python, R, SQL

Admission Process

Fill in the Application Form 1
Submit the Documents 2
Pay the
Admission Fee
3

Career Opportunities

Software Developer

Data Scientist

System Analyst

IT Project Manager

Cybersecurity Analyst

Cloud Solutions Architect

Artificial Intelligence/Machine Learning Engineer

Frequently Asked Questions ?

This program combines academic learning with real-world work experience in data science. Students study advanced concepts while working on live projects in industries, preparing them for data-driven careers.

In addition to theoretical learning, this program includes on-the-job training with industry partners. It focuses on applying data science skills in real-world scenarios, making you job-ready.

No, prior work experience is not mandatory. The program is designed to equip you with the necessary skills and provide hands-on industry exposure, even if you are a fresher.

The curriculum includes machine learning, big data analytics, data visualisation, programming languages like Python and R, database management, and cloud computing, among other advanced topics.