Master of Science in Data ScienceHome / Master of Science in Data Science

Advanced Data Science Knowledge: Apply advanced concepts of data science, statistics, machine learning, and computational intelligence to solve complex real-world problems.

Data Engineering & Computational Skills: Design and implement scalable data engineering solutions using modern programming languages, cloud platforms, and distributed computing frameworks.

Analytical Thinking & Problem Solving: Analyze large and complex datasets using critical thinking, statistical inference, and optimization techniques to support data-driven decision-making.

Machine Learning & AI Model Development: Develop, evaluate, and deploy machine learning, deep learning, and AI models for predictive analytics and intelligent automation.

Data Visualization & Communication: Communicate analytical findings effectively through professional reports, research publications, dashboards, and data storytelling methods.

Ethics, Privacy & Professional Responsibility: Evaluate ethical, legal, privacy, and security issues related to data collection, processing, and AI deployment in societal and industrial contexts.

Interdisciplinary Applications & Industry Alignment: Integrate data science solutions across domains such as healthcare, finance, manufacturing, smart cities, biotechnology, and social sciences.

Research Aptitude & Lifelong Learning: Demonstrate research competence, innovation, and continuous learning for pursuing Ph.D., entrepreneurship, and emerging technologies in data science.

• Advanced Statistical & Mathematical Modelling: Apply advanced statistical techniques, machine learning theory, optimization, and probabilistic modelling for complex data analysis.
• Big Data Analytics & Data Engineering: Design and manage big data pipelines using tools such as Hadoop, Spark, NoSQL databases, and cloud-based architectures.
• AI, Deep Learning & Intelligent Systems: Develop deep learning models and AI-driven applications using neural networks, NLP, computer vision, and reinforcement learning approaches.
• Business Intelligence & Decision Support Systems: Build decision-support solutions using data visualization, dashboards, and predictive analytics for strategic organizational planning.
• Research-Based Project & Industry Solutions: Execute industry-oriented projects and research dissertations involving real-world datasets, model deployment, and scholarly reporting.

A two-year, four-semester program combining core courses, electives, internships, viva and dissertation. The curriculum follows UGC guidelines and emphasizes experiential learning through labs, projects, simulations, workshops and industry engagement.

• Internships: 1^st to 3^rd semester
• Dissertation / Project: Entire 4^th Semester
• Discipline Specific Electives & Skill/Ability Enhancement Courses

Evaluation

The overall assessment comprises an Internal Assessment (60% weightage) and an External End-Semester Examination (ESE, 40% weightage). The Internal Assessment is split into a Mid-Semester Examination (MSE) and Continuous Evaluation Components (CEC). Each theory course carries 100 marks, while practical courses are evaluated out of 50 marks. CEC evaluations include MCQ tests, open-book exams, assignments, article reviews, oral presentations, and short projects.

Courses

The curriculum of the program is based on the UGC prescribed curriculum structure and as per NEP 2020 policy. The courses and allied credits are distributed in major, minor, inter-multidisciplinary, ability/skill enhancement, research, etc. categories as per the prescribed standards.

To acquire the degree in M.Sc. Data Science, a student must study and pass all compulsory courses with specified credits. For theory classes, one credit indicates one-hour lecture per week, for tutorial sessions, one credit indicates one-hour session per week, while for practical sessions, one credit indicates two-hours of practical/laboratory/hands-on session per week.

A student has to earn a minimum of 96 Credits to get a degree in M.Sc. Data Science.

Students have to undergo Internship after the completion of end-semester examination of 1^st, 2^nd and 3^rd Semesters. The internship carries a weightage of two(2) Credits. Dissertation/project/On-job training(OJT) is offered in the final Semester. .

GSFC University provides hands-on training to its students through highly-equipped laboratories for the courses offered in respective programs

Research Labs: Exposure of working on industrial problems in specialized laboratories sponsored and supported by Gujarat Council on Science & Technology (GUJCOST), Department of Science & Technology (DST)

• Supercomputer Lab (PARAM Shavak DL-GPU)
• Design IoT Lab

Core Courses Labs: Laboratories for core & specialized courses:

• Data Science Lab
• Business analytics Lab
• Advance Data Science Lab
• Data Engineering Lab
• AI & ML Lab
• Robotics & Automation Lab
• Operating System Lab
• Programming Lab
• Digital Electronics & Microprocessor Lab
• Research & Development Lab
• Cyber Security Lab

E Yantra Lab: Collaboration with IIT Bombay

Access to GSFC Ltd laboratories: Prospects of working at the laboratories of GSFC Limited and access to of 22 process plants for internship opportunities as well as learning from the industry experts

• Total Intake:10 Seats
• Mode of Admission: Merit Based
• Qualifying Examination: A Bachelor’s Degree in Science or Technology or Computer Applications from a recognized University

Eligibility for Admission

Candidates with ≥55% in B.Sc./B.E./B.Tech/BCA are eligible for direct admission through the interview process. The candidate must register through the University website for getting notified for the interview process.

• Final-year students from eligible disciplines may apply
• 20% seats reserved for GSFC students; 80% open on All-India basis
• Admissions are merit-based, with provision for re-test and category conversion as per norms

Eligible backgrounds include Statistics, Mathematics, Physics, Computer Science, Economics, Econometrics, Operational Research, Engineering (CS/IT/Electronics/Electrical), BCA, B.Sc. (IT), and B.Sc. (Data Science). Final-year students may also apply, subject to submission of results.

Registration Fees

The registration fee for submitting an online application form is Rs. 600/- (Rupees Six Hundred Only), which is to be paid online.Apply Now

Program Brochure

University Brochure

Detailed Curriculum