M.Sc. (Data Science)
M.Sc. (Data Science) is a 2 years (Four Semester) full-time choice based programme offered by the Department. The M. Sc. (Data Science) course admission took place at the Department of Computer Science in the month of June every year (after declaration of the result of the B.Sc.). The Admission to the said course will be made on the basis of Entrance Test conducted by the Department.
Eligibility & Entrance Test
A candidate with minimum 50% score in Graduation can appear for Entrance Test through which the admission merit list will be generated.
M.Sc. (Data Science) Entrance Test Syllabus
Intake Capacity & Reservation
The Intake capacity of the Department for M.Sc. (Data Science) is 120 Stduents.
The reservation in the seats is as per the rules and regulations of Government of Maharashtra and University of Mumbai.
For International Students, 15% quota in addition to the sanctioned intake of seats has been granted vide University circular no. Aff./Recog.I/232 of 2011 dated 30th July, 2011. Intake- 120 Students * 15% = 18 Foreign Students.
The provision of 2 (two) supernumerary seats for students from Jammu & Kashmir are made vide University circular no. Aff./ICC/2012-13/22 dated 8th January, 2013.
Fees
| M.Sc. (Data Science) Semester - I & II | M.Sc. (Data Science) Semester - III & IV | ||
|---|---|---|---|
| GEN/DT/NT/OBC/SBC Category | INR 34455.00 | GEN/DT/NT/OBC/SBC Category | INR 35430.00 |
| SC/ST Category | INR 1625.00 | SC/ST Category | INR 1600.00 |
| Foreign Student | INR 94455.00 | Foreign Student | INR 95430.00 |
Syllabus and Credit Scheme
| Course Code | Course Name | Marks | Credits |
| 1113061 : M.Sc. (Data Science) Semester-I | |||
|---|---|---|---|
| 501 | Essential Technolgies for Data Science | 100 | 4 |
| 502 | Practical: Essential Technolgies for Data Science | 50 | 2 |
| 503 | Data Analytsis & Visualization | 100 | 4 |
| 504 | Practical: Data Analytsis & Visualization | 50 | 2 |
| 505 | Statistical Methods for Data Science | 50 | 2 |
| 506a | Elective: SPARK Technologies | 50 | 2 |
| 506b | Elective: Retail Marketing Analytics | 50 | 2 |
| 506c | Elective: Sports Data Analytics | 50 | 2 |
| Practical: Elective - SPARK Technologies or Retail Marketing Analytics or Sports Data Analytics | 50 | 2 | |
| 510 | Research Methodology | 100 | 4 |
| Total | 550 | 22 | |
| 1113062 : M.Sc. (Data Science) Semester-II | |||
| 511 | Soft Computing | 100 | 4 |
| 512 | Practical: Soft Computing | 50 | 2 |
| 513 | Time Series Analysis & Forecasting | 100 | 4 |
| 514 | Practical: Time Series Analysis & Forecasting | 50 | 2 |
| 515 | Ethical Issues in Data Science | 50 | 2 |
| 516a | Elective: Human Resource Analytics | 50 | 2 |
| 516b | Elective: Public Health Care Analytics | 50 | 2 |
| 516c | Elective: Social Media Analytics | 50 | 2 |
| Practical: Elective - Human Resource Analytics or Public Health Care Analytics or Social Media Analytics | 50 | 1 | |
| 517 | On Job Training | 100 | 4 |
| Total | 550 | 22 | |
| 1113063 : M.Sc. (Data Science) Semester-III | |||
| 601 | Next Generation Databases | 100 | 4 |
| 602 | Practical: Next Generation Databases | 50 | 2 |
| 603 | Text Mining & Natural Language Processing | 100 | 4 |
| 604 | Practical: Text Mining & Natural Language Processing | 50 | 2 |
| 605 | Data Compliance & Auditing | 50 | 2 |
| 606a | Elective: Image & Video Analytics | 50 | 2 |
| 606b | Elective: Econometrics & Finance | 50 | 2 |
| 606c | Elective: Data Science for Agriculture | 50 | 2 |
| Practical: Elective - Image & Video Analytics or Econometrics & Finance or Data Science for Agriculture | 50 | 2 | |
| 607 | Research Project | 100 | 4 |
| Total | 550 | 22 | |
| 1113064 : M.Sc. (Data Science) Semester-IV | |||
| 611 | Deep Neural Networks | 100 | 4 |
| 612 | Practical: Deep Neural Networks | 50 | 2 |
| 613 | Optimization Methods for Data Science | 100 | 4 |
| 614 | Practical:Optimization Methods for Data Science | 50 | 2 |
| 615a | Elective: Blockchain Technologies for Data Science | 50 | 2 |
| 615b | Elective: Financial Risk Analytics & Management | 50 | 2 |
| 615c | Elective: Legal Analytics | 50 | 2 |
| Practical: Blockchain Technologies for Data Science or Financial Risk Analytics & Management or Legal Analytics | 50 | 2 | |
| 616 | Research Project | 150 | 6 |
| Total | 550 | 22 | |
| Grand Total | 2200 | 88 | |
Examination Scheme
The Internal Examination based on the tests and presentations are of 50 marks in each paper. The final University Examination shall be of 2 hours duration for each theory papers of 50 marks and 2 hours duration for each practical papers of 50 marks.
To pass the M.Sc. Examination a candidate must obtain a minimum of 40% of the marks allotted to each paper (Internal, Theory and Practical Examination).