About the Programme
Master of Data Science (MDS) is a two-year postgraduate program designed to develop expertise in data-driven decision-making through an interdisciplinary blend of Statistics, Computer Science, and Analytics. The program emphasizes both theoretical foundations and practical applications of data science using industry-relevant tools and technologies. Students gain hands-on experience through projects, internships, case studies, and research-oriented learning. The curriculum integrates emerging areas such as Artificial Intelligence, Machine Learning, and Big Data Analytics to prepare learners for evolving industry and research demands. With opportunities for specialization, collaborative learning, and industry interaction, the program equips students for careers in academia, research, analytics, and technology-driven organizations. Students can pursue a 1+1 Systems Science pathway with Binghamton University and graduate with dual degrees and international academic exposure.
Interdisciplinary Learning
Combines Computer Science and Data Science to build strong computational, analytical, and problem-solving skills.
Industry-Focused Curriculum
Covers emerging technologies including Artificial Intelligence, Machine Learning, and Big Data Analytics aligned with global industry standards.
Hands-on Technical Experience
Provides practical exposure through projects, labs, case studies, and real-world application-based learning experiences.
Industry and Research Opportunities
Offers advanced specialization and research pathways for higher studies, innovation, and industry-oriented expertise.
Why Choose This Programme?
Academic Excellence & Research
Integrates theoretical knowledge, practical learning, and research-oriented academic experiences.
Industry-Standard Toolkits
Develops expertise in modern data science tools for solving real-world challenges.
Career Readiness & Exposure
Enhances employability through electives, industry exposure, projects, and hands-on training opportunities.
Advanced Problem Solving
Strengthens analytical thinking and advanced problem-solving skills in data science applications.
Ethics & Lifelong Learning
Encourages ethical practices, professional responsibility, collaboration, and lifelong learning attitudes.
Leadership & Communication
Builds leadership, communication, and teamwork skills for multidisciplinary professional environments.
Choose Your Track
This track covers foundational data science, machine learning, deep learning, GenAI, and quantum computing. It prepares graduates for roles like ML/AI Engineer and GenAI Specialist.
Focusing on R programming, advanced regression, econometrics, and Bayesian statistics, this track trains students for analytical career outcomes like Data Scientist, Quantitative Analyst, and Risk Analyst
Blending full-stack development, IoT, geospatial analytics, and cloud infrastructure, this track equips students for high-demand roles including Big Data Engineer and Cloud Data Engineer
What You Will Learn
Programme Structure
The programme structure outlines the academic curriculum designed to provide a systematic progression of learning through core subjects, electives, and practical components across semesters, ensuring both theoretical understanding and skill development.
Trimester 1 — Mathematical Foundations and Programming for Data Science
Trimester 2 — Algorithms, Databases, and Cloud Technologies
Trimester 3 — Intelligent Data Modelling and Research Applications
Trimester 4 — Neural Networks and Intelligent Data Systems
Trimester 5 — Big Data, Reinforcement Learning, and Specialized Analytics
Trimester 6 — Applied Research and Industry Integration in Data Science
Eligibility & Fee Structure
Career Paths
Your Career Roadmap
Select a specialisation track to explore the learning journey and career outcomes tailored to your chosen domain.
Research Methods in Data Science, Mathematical Foundations for Data Science, Probability & Distribution Theory, Programming using Python, Design & Analysis of Algorithms, Database Technologies, Cloud Services.
Machine Learning, Neural Networks & Deep Learning, Applied GenAI, Natural Language Processing, Data-driven Modelling & Visualization, Time Series & Forecasting Techniques, Research Problem Identification.
Reinforcement Learning, Quantum Machine Learning, Big Data Analytics, Image & Video Analytics, Industry Project, Research Dissertation, Advanced AI Research Applications.
Research Methods in Data Science, Probability & Distribution Theory, Inferential Statistics using R, Database Technologies, Design & Analysis of Algorithms, Mathematical Foundations for Data Science.
Regression Modelling, Machine Learning, Time Series & Forecasting Techniques, Data-driven Modelling & Visualization, Applied Statistical Analysis, Research Problem Identification.
Econometrics, Bayesian Statistics, Bio-Statistics, Big Data Analytics, Graph Analytics, Research Modelling, Industry Project.
Data Scientist|Quantitative Analyst|Risk Analyst|Decision Scientist|Business Analytics Consultant|Statistical Analyst|Forecasting Analyst|Analytics Strategist
IoT Analytics, Image & Video Analytics, Neural Networks & Deep Learning, Machine Learning, Java Programming, Data-driven Modelling & Visualization.
Big Data Analytics, Geospatial Data Analytics, Quantum Machine Learning, Graph Analytics, Industry Project, Research Dissertation, Advanced Computational Research.
Message from the HOD
Pune Lavasa Campus
Greetings from the Department of Statistics and Data Science!
The Department of Statistics and Data Science at CHRIST (Deemed to be University), Pune Lavasa Campus is an intellectually vibrant space where Data Science, Economics, Mathematics and Statistics come together to build the foundations of analytical thinking and innovation. Known as “The Hub of Analytics,” the Lavasa Campus provides an ecosystem that encourages exploration, experimentation, and interdisciplinary learning. Our programs are designed to combine theoretica
Message from the HOD
Greetings from the Department of Statistics and Data Science!
The Department of Statistics and Data Science at CHRIST (Deemed to be University), Pune Lavasa Campus is an intellectually vibrant space where Data Science, Economics, Mathematics and Statistics come together to build the foundations of analytical thinking and innovation. Known as “The Hub of Analytics,” the Lavasa Campus provides an ecosystem that encourages exploration, experimentation, and interdisciplinary learning. Our programs are designed to combine theoretical depth with practical application, preparing students to translate data into actionable insights. Through a blend of classroom learning, industry internships, live research projects, and case-based studies, students gain hands-on experience in applying analytical methods to real-world challenges. Faculty members with strong research and industry backgrounds mentor students closely, fostering curiosity, precision, and creativity.
The department also promotes active engagement through technical clubs, hackathons, seminars, and collaborative research initiatives, helping students stay aligned with emerging trends in analytics, economics, and data-driven decision-making.
At the heart of our philosophy is the belief that data is more than numbers—it’s a way to understand people, policies, and progress. We aim to nurture professionals who are not only skilled analysts but also thoughtful contributors to society’s evolving digital and economic landscape.
Admission Process
- Register with your Email ID
- Login to the Admission Portal
- Fill the Application Form
- Pay Application Fee
- Entrance Test (If Applicable)
- Assessment
- Interview
- Check login page for result
- If selected, Offer Letter attached
- Pay Course Fee Online
- Complete Admission Process
Ready to Apply?
Applications for the 2026 batch are open. Deadline: 12-Jun-2026.