About the Programme
The MSc in Data Science + MS in Systems Science is an international dual-degree programme offered in collaboration between CHRIST (Deemed to be University) and Binghamton University. Designed with a global academic structure, the programme follows a 1+1 model, where students complete the first year at CHRIST University, India, and the second year at Binghamton University, USA. The programme is crafted to build strong analytical, computational, and problem-solving skills required in today’s data-driven world. The curriculum combines core concepts in Data Science, Statistics, Machine Learning, and Systems Science with practical exposure to modern technologies such as Hadoop, Natural Language Processing (NLP), and Data Analytics. With a balanced focus on theory and application, students gain hands-on learning through projects, internships, research activities, guest lectures, and industry interactions. The interdisciplinary learning environment helps students understand complex systems, work with real-world data, and develop intelligent solutions across domains. The programme also offers international exposure, advanced research opportunities, and industry-relevant training, preparing graduates for careers in Data Science, Artificial Intelligence, Business Analytics, Systems Engineering, and related fields. By integrating academic excellence with practical learning, the programme aims to develop future-ready professionals equipped for the global technology landscape.
Global Dual-Degree Experience
Gain international academic exposure through a unique 1+1 programme offered in collaboration with Binghamton University and CHRIST (Deemed to be University).
Industry-Oriented Curriculum
Learn emerging technologies such as Artificial Intelligence, Machine Learning, Big Data Analytics, Hadoop, and Natural Language Processing aligned with global industry needs.
Hands-on Practical Learning
Develop real-world skills through projects, internships, laboratory sessions, research activities, and application-based learning experiences.
Research and Career Advancement
Build strong analytical and problem-solving abilities with opportunities for research, innovation, and careers in Data Science, AI, Business Analytics, and Systems Science.
Why Choose This Programme?
Academic Excellence
Integrates theoretical knowledge, practical learning, and research-oriented academic experiences.
Practical Toolkits
Develops expertise in modern data science tools for solving real-world challenges.
Career Readiness
Enhances employability through electives, industry exposure, projects, and hands-on training opportunities.
Analytical Thinking
Strengthens analytical thinking and advanced problem-solving skills in data science applications.
Professional Ethics
Encourages ethical practices, professional responsibility, collaboration, and lifelong learning attitudes.
Leadership Skills
Builds leadership, communication, and teamwork skills for multidisciplinary professional environments.
Choose Your Track
This future-ready program bridges advanced data science, computational theory, and professional research practices. Across all areas of study, students build a rigorous foundation in database technologies, programming, and algorithmic design before advancing to high-impact industry projects, corporate internships, and specialized dissertations. The curriculum is meticulously structured to cultivate elite technical expertise, analytical thinking, and leadership readiness for the global technology and research landscape.
Integrates rigorous mathematical foundations with advanced computational intelligence. Students progress from database technologies to deep learning, generative AI, and quantum computing, culminating in a research dissertation tailored for elite global tech and research leadership roles.
Transforms complex data into strategic organizational decisions. This curriculum combines advanced statistical modeling, time-series forecasting, and simulation with econometrics and operations research to optimize risk management and strategic corporate planning across global industries.
Explores interconnected digital ecosystems by merging data science with advanced network theory. Students master IoT, big data, and graph analytics to effectively analyze, manage, and secure large-scale corporate infrastructure and modern technology networks.
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 — Systems Science Dual Degree (BU)
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.
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 Generative AI, Natural Language Processing, Data-driven Modelling & Visualization, Research Problem Identification.
Reinforcement Learning, Quantum Machine Learning, Foundations of Neural Networks, Industry Project, Research Dissertation, Advanced AI Research Applications.
Research Methods in Data Science, Probability & Distribution Theory, Inferential Statistics using R, Design & Analysis of Algorithms, Database Technologies.
Regression Modelling, Time Series & Forecasting Techniques, Machine Learning, Modeling & Simulation, Applied Probability & Statistics, Data Visualization.
Econometrics, Bayesian Statistics, Operations Research, Applied Multivariate Data Analysis, Research Modelling, Industry Project.
Programming using Python, Full Stack Web Development, Database Technologies, Cloud Services, Design & Analysis of Algorithms.
IoT Analytics, Image & Video Analytics, Neural Networks & Deep Learning, Machine Learning, Collective Dynamics of Complex Systems.
Big Data Analytics, Graph Analytics, Advanced Topics in Network Science, Geospatial Data Analytics, Industry Project, Research Dissertation.
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.