Candidate must have completed bachelor's degree in B.A./BCA/B.Sc. (Statistics or Mathematics or Computer Science) /B.E/B.Tech.
*Earnings depend on role, industry, company policies, and internship availability.
Our work-integrated degree program lets you gain practical work experience through internships, while completing your degree with Chandigarh University.
The M.Sc Data Science Work-Linked Degree 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.
Practical Data Analytics: Gain hands-on experience in data analysis, machine learning, and statistical modeling.
Industry Collaboration: Work with leading companies while pursuing your degree to apply data science skills in real-world settings.
Comprehensive Curriculum: Learn data science techniques, programming, and advanced analytics tools.
Earn While You Learn: Receive work experience and a stipend while completing your academic studies.
Career-Ready Skills: Graduate with a portfolio of projects and industry experience to excel in the data science field.
Master Core Data Science Concepts: Gain a deep understanding of data analysis, machine learning, and statistical modeling.
Learn Data Visualization: Acquire skills to create impactful visual representations of complex data.
Integrate Theory with Practice: Solve real-world problems by applying data science techniques in industry settings.
Enhance Problem-Solving Skills: Develop the ability to analyze, interpret, and provide actionable insights from data.
Focus on Industry-Relevant Applications: Gain knowledge of data science applications across sectors such as finance, healthcare, and technology.
Data Analysis Proficiency: Demonstrate the ability to process, analyze, and interpret large datasets for informed decision-making.
Practical Machine Learning Expertise: Implement machine learning models to solve complex, real-world problems effectively.
Professional Problem-Solving: Apply data science methodologies to deliver solutions in industry-specific scenarios.
Real-World Project Experience: Graduate with a portfolio showcasing applied data science projects and industry assignments.
Workplace Competency: Exhibit technical, analytical, and teamwork skills, ready to excel in professional data science roles.
| 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 |
| Master of Science (Data Science) | SEM I | SEM II | SEM III | SEM IV |
| Course Fee (Discounted) | 27,500 | 27,500 | 27,500 | 27,500 |
Data Scientist
Data Analyst
Big Data Engineer
AI Specialist
Data Architect
Machine Learning Engineer
Business Intelligence Analyst
