MSc Data Science
- Home
- MSc Data Science
Eligibility Conditions (Graduates from recognized University)
- Graduates in BCA /B.Sc (IT/CS/IS)/ AMIE/ BE (CS/IS/Electronics/ IT / EEE / CSE / ISE / TE) /B.Tech (CS/IS/IT/Electronics) or any other related courses/subjects from any recognized university.
OR
- Graduates in B.Sc with mathematics/statistics as one of the major
Duration: 2 Years
Scheme: Semester ( CBCS)
Credits: 82
Course Matrix
M.Sc. in Data Science (CBCS mode)
Sem | Course Code
| Course Title | Credits | Counseling/PCP Hours | Max. Marks | Min. Passing Marks | Duration of Exam | |||
Internal Assessment | Term end exam | Total Marks | Internal Assessment | Term end exam | ||||||
I | MDDSC-1.1 | Mathematical Foundations | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 |
MDDSC-1.2 | Programming with Python | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSC-1.3 | Mathematical Foundations Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSC-1.4 | Programming with Python Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSE-1.5 | Database Management System | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSE-1.6 | Data Structure | |||||||||
MDDSE-1.7 | Operating System | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
ELMIT –01 | Interdisciplinary Elective-1 Green Computing | 2 | 06 | 10 | 40 | 50 | 04 | 16 | 11/2 | |
Total | 20 | 168 | 110 | 440 | 550 | 44 | 176 | – | ||
Note: Students are recommended to opt any TWO from MDDSE-1.5, MDDSE-1.6 OR MDDSE-1.7
Sem | Course Code
| Course Title | Credits | Counseling/PCP Hours | Max. Marks | Min. Passing Marks | Duration of Exam | |||
Internal Assessment | Term end exam | Total Marks | Internal Assessment | Term end exam | ||||||
II | MDDSC-2.1 | Foundations of Data Science | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 |
MDDSC-2.2 | Statistical Foundations and Inference | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSC-2.3 | Foundations of Data Science Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSC-2.4 | Statistical Foundations and Inference Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSE-2.5 | Data Mining and Data Warehousing | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSE-2.6 | Data Security and Privacy | |||||||||
MDDSE-2.7 | Business Intelligence | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
ELMIT –02 | Interdisciplinary Elective-2 E-commerce | 2 | 06 | 10 | 40 | 50 | 04 | 16 | 11/2 | |
Total
| 20 | 168 | 110 | 440 | 550 | 44 | 176 | – | ||
Note: Students are recommended to opt any TWO from MDDSE-2.5, MDDSE-2.6 OR MDDSE-2.7
Sem | Course Code
| Course Title | Credits | Counseling/PCP Hours | Max. Marks | Min. Passing Marks | Duration of Exam | |||
Internal Assessment | Term end exam | Total Marks | Internal Assessment | Term end exam | ||||||
III | MDDSC-3.1 | Artificial Intelligence | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 |
MDDSC-3.2 | Big Data Analytics | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSC-3.3 | Artificial Intelligence Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSC-3.4 | Big Data Analytics Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSE-3.5 | Cloud Computing | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSE-3.6 | Social Network Analysis | |||||||||
MDDSE-3.7 | Internet of Things | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDSEC-1 | R Programming | 2 | 06 | 10 | 40 | 50 | 04 | 16 | 11/2 | |
Total | 20 | 168 | 110 | 440 | 550 | 44 | 176 | – | ||
Note: Students are recommended to opt any TWO from MDDSE-3.5, MDDSE-3.6 OR MDDSE-3.7
Sem | Course Code
| Course Title | Credits | Counseling/PCP Hours | Max. Marks | Min. Passing Marks | Duration of Exam | |||
Internal Assessment | Term end exam | Total Marks | Internal Assessment | Term end exam | ||||||
IV | MDDSC-4.1 | Machine Learning. | 4 | 12 | 20 | 80 | 100 | 08 | 32 | 3 |
MDDSC-4.2 | Managerial and Entrepreneurship for Data Scientist | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSC-4.3 | Machine Learning Lab | 2 | 60 | 10 | 40 | 50 | 04 | 16 | 3 | |
MDDSC-4.4 | Dissertation | 8 | 240 | 30 | 120 | 150 | 12 | 48 | 3 | |
MDDSE-4.5 | Deep Learning | 3 | 09 | 20 | 80 | 100 | 08 | 32 | 3 | |
MDDSE-4.6 | Predictive Analysis | |||||||||
MDSEC-2 | Tableau | 2 | 06 | 10 | 40 | 50 | 04 | 16 | 11/2 | |
Total | 22 | 336 | 110 | 440 | 550 | 44 | 176 | – | ||
Note: Students are recommended to opt any ONE from MDDSE-4.5 OR MDDSE-4.6
MDDSC-4.4- Dissertation/Project work (Implementation).
* Viva-voce is a compulsory component of Dissertation
DSC: Discipline Specific Core; DSE: Discipline Specific Elective; SEC: Skill Enhancement
Course
Note: Course exemption- 40% marks including the Internal Assessment