MS/M.Phil Data Science: 2-Year, 4-Semester Program (30 Credit Hours)

The MS/MPhil Data Science program is designed to train students in the rapidly growing field of data science which lies at the intersection of statistical methodologies, computational science, and several wide-ranging application domains. The curriculum is based on core data science courses and technical electives providing opportunities to build knowledge and professional skills in various data science areas that are highly sought after in the current job market. Students will get a comprehensive overview of data science procedures, in addition to statistical methodologies and machine learning techniques for data science.

During the program students will gain and build upon theoretical and conceptual foundations of key data science tasks, as well as learn to use data analysis tools to discover hidden useful patterns and relationships in data. The program will equip students to process large and complex data sets through computational, statistical and machine learning techniques, thereby extract knowledge and gain actionable insights from huge amounts of data.

Eligibility:

• 16-year Bachelor’s Degree in IT, SE, CS, Electronics, Telecom, Statistics, Mathematics or Engineering.
• Minimum 2.40/4.0 CGPA or 50% marks (annual system).

Pre-requisite: Pre-entry test and interview.

Note: Having passed 1st semester course work with GPA 3.0 or above, students are eligible to start research while the 2nd semester coursework is in progress.

Deficiency Courses:

• Programming Fundamentals
• Data Structures & Algorithms OR Design and Analysis of Algorithms
• Database Systems

Semester I

S.No.	Course Title	Cr. Hrs.
1	Data Science: Tools & Techniques (Core - I)	3 (2 1)
2	Statistical and Mathematical Methods for Data Science	3
3	Elective I	3
4	Elective II	3
Semester Total		12

Semester II

S.No.	Course Title	Cr. Hrs.
1	Research Methodology (Core - III)	3
2	Machine Learning (Core - IV)	3
3	Elective III	3
4	Elective IV	3
Semester Total		12
Total Course Credits		24

3rd to 4th Semester:

Research on the approved topic and thesis/dissertation write-up and its defense (06 Credit Hours).

Elective Courses:

S.No	Course Title	Credit Hours
1	Advanced Computer Vision	3
2	Advanced Database Management Systems	3
3	Bayesian Data Analysis	3
4	Big Data Analytics	3
5	Bioinformatics	3
6	Cloud Computing	3
7	Computational Genomics	3
8	Data Engineering	3
9	Data Mining	3
10	Data Visualization	3