About the Programme
The Bachelor of Science (Computer Science, Data Science / Honours / Honours with Research) is a dual major program that offers a comprehensive education, blending computer science fundamentals with advanced data science techniques. This interdisciplinary approach equips students with algorithmic and analytical skills for data-driven problem-solving and decision-making. Aligned with top global standards, the curriculum includes hands-on projects in AI, machine learning, and big data analytics. With Honours and Research tracks, students gain deeper expertise, positioning them to make impactful contributions in both academic and industry settings.
Industry-Oriented Curriculum
The programmes integrate emerging technologies and practical applications to prepare students for current industry demands.
Research and Innovation
The department fosters a strong research culture that encourages innovation and interdisciplinary problem-solving.
Experiential Learning Opportunities
Students gain hands-on experience through internships, projects, competitions, and industry collaborations.
Career and Higher Education Prospects
The programmes prepare graduates for diverse professional careers and advanced studies in data science, analytics, and research.
Why Choose This Programme?
Interdisciplinary Learning Approach
Integrates statistics, computing, economics, and mathematics for versatile analytical problem-solving skills.
Industry-Relevant Curriculum
Covers AI, machine learning, visualization, and analytics aligned with current industry demands.
Hands-on Practical Exposure
Provides internships, projects, workshops, and hackathons for practical technical learning experiences.
Research and Innovation Opportunities
Encourages research, publications, conferences, and interdisciplinary innovation in emerging data science fields.
Expert Faculty and Mentorship
Experienced faculty provide mentorship, industry exposure, and practical technology-oriented learning guidance.
Excellent Career and Higher Education Prospects
Prepares students for analytics careers, higher studies, and advanced research opportunities.
Choose Your Track
Focus on data-driven technologies, artificial intelligence, machine learning, and analytical decision-making using computational and statistical methods.
Focus on data-driven technologies, artificial intelligence, machine learning, and analytical decision-making using computational and statistical methods.
Build expertise in software development, intelligent systems, cloud technologies, and modern computing architectures.
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.
Semester 1 — Building Foundations in Computational Sciences
Semester 2 — Computational Problem Solving and Data Exploration
Semester 3 — Core Concepts in AI, Databases, and Analytical Systems
Semester 4 — Computational Intelligence and Networked Systems
Semester 5 — Emerging Technologies and Data-Driven Intelligence
Semester 6 — Next-Generation Technologies and Intelligent Computing
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.
Computer Systems Fundamentals, Data Science Principles, Algorithmic Problem Solving in C, Web Technologies, Data Structures & Algorithms, Python for Scientific Programming, Probability Distribution Theory, Data Mining & Exploratory Data Analysis
Operating Systems, Database Management Systems, Soft Computing & Artificial Intelligence, Sampling Estimation & Hypothesis Testing, Linear Algebra, Full Stack Web Development, Computer Networks & Communication Protocols, Machine Learning: Supervised Techniques
Advanced Machine Learning & Neural Networks, Cloud Computing & Virtualisation, Deep Learning Models, Natural Language Processing, Big Data Analytics, AR/VR, IoT, Quantum Computing, Internship, Mini Project & Research-Based Applications
Computer Systems Fundamentals, Algorithmic Problem Solving in C, Web Technologies, Data Structures & Algorithms, Python for Scientific and Computational Programming, Data Mining & Exploratory Data Analysis, Discrete Mathematics, Probability Distribution Theory & Applications
Operating Systems, Database Management Systems, Soft Computing & Artificial Intelligence, Sampling Estimation & Hypothesis Testing, Linear Algebra, Full Stack Web Development, Computer Networks & Communication Protocols, Machine Learning: Supervised Techniques
Analysis and Design of Algorithms, Advanced Machine Learning & Neural Networks, Cloud Computing & Virtualisation, Deep Learning Models, Digital Image Processing & Image Analytics, Microservices Architectures & APIs, Mobile Application Development, Embedded Systems & IoT, 5G Networks and Beyond, Mini Project & Internship
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.