Programmes

Master of Science (Data Science)

This programme will equip students with data science knowledge highly relevant in intelligence era. This programme aims to provide a comprehensive framework for understanding data science life cycle, statistical foundations, technologies and applications.

Duration (in months): 24 (Full time)

Eligibility: Graduate from any recognized University/ Institution of National Importance with a minimum of 50% marks or equivalent grade (45% marks or equivalent grade for Scheduled Caste / Scheduled Tribes).

Medium of Instruction: English

Programme Pattern : Semester

Course and Specialization : As per Annexure A

Fee :

Academic Fee p.a Institute Deposit Total
Indian Students
International Students
(Under EVBAB)

Assessment :All courses will have 30% internal component and 70%component as external [University] examination.

Standard of Passing :The assessment of the student for each examination is done, based on relative performance. Maximum Grade Point (GP) is 10 corresponding to O (outstanding). For all courses, a student is required to pass both internal and external examination separately with a minimum Grade Point of 4 corresponding to Grade P. Students securing less than 40% absolute marks in each head of passing will be declared FAIL. The University awards a degree to the student who has achieved a minimum CGPA of 4 out of maximum of 10 CGPA for the programme.

Award of Degree/Diploma/Certificate :Master of Science (Data Science) will be awarded at the endof semester IV examination by taking into consideration the performance of all semester examinations after obtaining minimum 4.00 CGPA out of 10 CGPA.

Classification of Credits

Semester Genric Core Generic Elective Specialization Core Specialization Elective Open Elective Audit Total
1 19 0 0 0 0 0 19
2 21 0 0 0 0 0 21
3 13 3 0 0 6 0 19
4 15 0 0 0 6 0 21
Total 68 0 0 0 12 0 80


Annexure A

Catalog Course Code Course Code Course Title Specialization Credit Internal Marks External Marks Total Marks
Semester : 1
Generic Core Courses
T6688 0301420101 Statistical computing 4 60 140 200
T4725 0301420102 Research Methodology 2 30 70 100
T3577 0301420103 Data Analysis Using Python 2 30 70 100
T3356 0301420104 NOSQL Databases 3 45 105 150
T3281 0301420105 PData Warehousing 3 45 105 150
T3364 0301420106 Data Management 3 45 105 150
T3637 0301420107 Mathematics Foundations 2 30 70 100
Total 19 285 665 950
Semester : 2
Generic Core Courses
T6699 0301420201 Multivariate statistics-1 4 60 140 200
T6697 0301420202 Statistical Inference 4 60 140 200
T3579 0301420203 Machine Learning Algorithms 4 60 140 200
T3448 0301420204 Text Analytics 3 45 105 150
T3683 0301420205 Operations Research and Optimization Techniques 2 30 70 100
T3455 0301420206 Data protection and Privacy 2 30 70 100
T3445 0301420207 Data Mining 2 30 70 100
Total 21 315 735 1050
Semester : 3
Generic Core Courses
T6701 0301420301 Multivariate statistical Analysis-2 4 60 140 200
T3566 0301420302 Artificial Neural Network and Deep Learning 3 45 105 150
T3567 0301420303 Data Analysis and Visualization 3 45 105 150
T3309 0301420304 Big data analytics 3 45 105 150
Total Required Credits 13 195 455 650
Generic Elective Courses Group
T3268 0301420305 Fuzzy Logic Data Science 3 45 105 150
T3568 0301420306 Natural Language Processing Data Science 3 45 105 150
F0003 0301420307 Advanced Data Mining Data Science 3 45 105 150
T3015 0301420308 Cognitive computing Data Science 3 45 105 150
Total Required Credits 6 90 210 300
Semester : 4
Generic Core Courses
T6725 0301420401 Time Series Analysis 3 45 105 150
0301420402 Project 12 180 420 600
Total 16 225 525 750
Generic Elective
T3558 0301420403 Reinforcement learning Data Science 3 45 105 150
T3134 0301420404 Social media and web analytics Data Science 3 45 105 150
T3560 0301420405 Computer vision Data Science 3 45 105 150
T3506 0301420406 Analytics applications Data Science 3 45 105 150
Total Required Credits 6 90 210 300

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