- Duration
- 2 years / 4 semesters
- Entry requirements
- Mathematics requires mathematics in the bachelor’s degree. Data Science lists relevant science, computing and engineering degrees or an equivalent degree with Mathematics, Statistics or Computer Science.
- Study format
- Online learning combines self-study materials with scheduled academic activities.
- Assessment
- Online proctored examinations; follow the university’s assessment instructions and announced schedule.
What you will study
Selected subject highlights from the saved programme information. Semester order and elective choices depend on the selected pathway.
- Syllabus, Eligibility, and Admission 2026 | Chandigarh University
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Subjects and pathways within this degree
Data Science
Work across data preparation, statistical reasoning and computational models. Useful analysis begins with a sound question and ends with an honest explanation of uncertainty, rather than a chart alone.
- Data Visualization
- Machine Learning
- Statistical Inference
Mathematics
Build depth in mathematical reasoning and structured problem solving. Proof, abstraction and applied techniques help learners work carefully with complex quantitative questions.
- Real Analysis
- Linear Algebra
- Topology
Data Analytics
Turn data into an explanation that a decision-maker can use. The central challenge is framing the right question, checking data quality and communicating what a result does and does not show.
- RAG Systems & Knowledge Engineering
- Pattern Recognition
Agentic AI
Study software systems that coordinate steps, tools and models to perform tasks. Designing such systems requires clear goals, evaluation and oversight so an automated workflow remains useful and predictable.
- Advanced NLP & Language Model Applications
- RAG Systems & Knowledge Engineering
Applied AI
Connect AI techniques with defined problems in products and services. A useful solution must be evaluated against the task it is meant to solve, including reliability and responsible use.
- Applied Deep Learning
- Natural Language Processing & Large Language Models
Generative AI
Explore systems that produce text, images or other content from learned patterns. Working effectively with these systems means understanding evaluation, retrieval, model behaviour and practical constraints.
- RAG Systems & Knowledge Engineering
- Large Language Models and Transformer Architectures
Computational Mathematics
Build depth in mathematical reasoning and structured problem solving. Proof, abstraction and applied techniques help learners work carefully with complex quantitative questions.
- Theory of Computation
- Optimal Control Theory
Applied Mathematics
Build depth in mathematical reasoning and structured problem solving. Proof, abstraction and applied techniques help learners work carefully with complex quantitative questions.
- Solid Mechanics
- Advanced Partial Differential Equations
Pure Mathematics
Build depth in mathematical reasoning and structured problem solving. Proof, abstraction and applied techniques help learners work carefully with complex quantitative questions.
- Number Theory
- Advanced Complex Analysis
Make the degree work for your goals
For graduates whose previous subjects match the programme’s requirements and who are comfortable with the expected quantitative or technical workload.
- Quantitative reasoning
- Scientific interpretation
- Technical problem-solving
- Research documentation
Choose a mathematical investigation or data-analysis exercise suited to your background. Record assumptions, methods and limitations clearly.
Your learning and assessment experience
Online learning combines self-study materials with scheduled academic activities.
University learner support and academic resources accompany the programme.
Online proctored examinations; follow the university’s assessment instructions and announced schedule.
Where this learning can take you
- Subject-related entry roles
- Further study
These are possible areas to explore, rather than promised placements or salaries. Your practical skills, previous experience and any additional professional requirements matter.
Plan the full commitment.
Talk through tuition, examination charges and instalment or EMI options for your chosen programme. Financing eligibility and provider terms apply.
From shortlist to application
- Choose the exact degree and subject pathway that match your goals.
- Match your qualifications to the programme’s entry requirements.
- Review the full fee quotation, academic calendar and refund terms.
- Use the university’s application process to submit documents and retain your admission confirmation.
Questions about this choice
What will I study in Master of Science?+
Choose between Data Science and Mathematics, each with its own entry requirements and published elective directions.
How should I plan study around work?+
Online learning combines self-study materials with scheduled academic activities. Reserve regular time for independent study and assessments, and compare the academic calendar with your working week.
Does career support guarantee a job?+
No. Use career services to prepare applications, practise interviews and build evidence of your skills. Employers make hiring decisions.
