M.Sc. Data Science
CURRICULUM BASED ON NEP 2020 GUIDELINES
Program Highlights
- Full Time.
- 2 years Course.
- Gaining Expertise in Machine Learning and AI
- Applying Data Science in Real-world Scenarios.
- Merit-based Admission through Entrance Score.
On Job Training/ Internship/ Project work.
Eligibility
- B.Sc. / B.C.A. (Science) / BE / B.Tech (50% marks for Open and 45% marks for Reserved category)
- Admission will be solely on the basis of marks obtained in the entrance test.
Why choose M.Sc. Data Science?
- To build a strong foundation in Data Science Principles
- To Develop Problem-Solving and Critical Thinking Skills
- To Gain Expertise in Machine Learning and AI
- To Build Teamwork and Project Management Abilities
- An Industry-focused curriculum designed in collaboration with experts to enhance learning
Career Opportunities
- Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, AI/Deep Learning Engineer, Quantitative Analyst (Quant), Research Scientist, Research Analyst, Business Analyst, NLP Specialist
- Emerging Roles such as Data Product Manager, MLOps Engineer, Customer Insights Analyst
- Ph.D. in Data Science, AI, or related fields, Entrepreneurship or freelancing in analytics/AI
Curriculum Highlights
- Core Subjects: Python Programming, Probability & Statistics, SQL for Data Science Machine Learning, Deep Learning and Big Data Analytics using PySpark.
- Exploratory Data Analysis (EDA), Time Series Analysis & forecasting, Web Scraping, Pattern Recognition, Data Integration & Engineering.
- Data Visualization: Reporting & Dashboard Design (Power BI/Tableau), Advanced & Interactive Visualizations, Real-Time Data Visualization.
- Emerging Trends: Cloud Computing in Data Science, Generative AI & NLP, Project Development, Data Science Model Building, CI/CD Pipeline.
- Skill Development Courses: Cyber Security, Human Rights, GitHub
Admission Process
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