Semester 3 | Semester 4 | Semester 5 | Semester 6 | Semester 7 | Semester 8 |
SCHEME-2 HSS-I (9-11) | SCHEME-3 EME (9-11) | MTH 442 (10) | SCHEME-4 HSS-II (9) | SCHEME-5 HSS-II (9) |
SCHEME-6 HSS-II (9) |
ESC201 (14) | MTH 211 (11) | MTH 441 (10) | MTH 422 (10) | DE – 1 (09) | DE – 4 (09) |
MTH301 (11) | MTH 210 (10) | ESO/SO-3: ESO 207 (12) | MTH 314 (10) | DE – 2 (09) | DE – 5 (09) |
ESO/SO-1: MSO 205 (11) | MTH 212M (1st half) (06) | ESO/SO-4: MSO 202M (1st half) (06) | MTH 312 (05) | DE – 3 (09) | OE-5 (09) |
MTH 207M - (2nd half) (06) | MTH 209 (05) | MTH 443 (10) | OE – 3 (09) | OE – 6 (09) | |
MTH 208 (05) | ESO/SO-2 (09) | OE-1 (09) | OE-2 (09) | OE – 4 (09) | |
56-58 | 50-52 | 47 | 53 | 54 | 45 |
Note: UGPs are NOT mandatory. However, depending on the consent of supervisor(s), a student may take up to 3 UGPs of 09 credits each against DE/OE (UGP will be counted as OE if taken outside the department as consented by the DUGC) requirements. A student can also take a 4^{th} UGP, that however will NOT be counted towards fulfilling the graduation requirements
List of Courses | |
Course No.: | Title |
MTH442 (3-0-1-0)[10] | Time Series Analysis |
MTH211 (3-1-0-0)[11] | Theory of Statistics |
MTH441 (3-0-1-0)[10] | Linear Regression and ANOVA |
MTH422 (3-0-1-0)[10] | Introduction to Bayesian Analysis |
MTH301 (3-1-0-0)[11] | Analysis – I |
MTH 210 (3-0-1-0)[10] | Statistical Computing |
ESO/SO-3: ESO 207 | Data Structures and Algorithms |
MTH 314 (3-0-1-0)[10] | Multivariate Analysis |
ESO/SO-1: MSO 205 (3-1-0-0)[11] | Introduction to Probability Theory |
MTH 212M (1st half) (3-1-0-0)[06] | Elementary Stochastic Processes I |
ESO/SO-4: MSO 202M (1st half) (3-1-0-0)[06] | Complex Analysis |
MTH 312 (1-0-2-0)[05] | Data Science Lab 3 |
MTH 207M - (2nd half) (3-1-0-0)[06] | Matrix Algebra and Linear Estimation |
MTH 209 (1-0-2-0)[05] | Data Science Lab 2 |
MTH 443 (3-0-1-0)[10] | Statistical & AI Techniques in Data Mining |
MTH 208 (0-0-3-2)[05] | Data Science Lab 1 |
Note: The department recommends PHY104 & PHY105 for the SDS students.
Note: (As per the Senate approved program) Up to 45 credits of internships in lieu of open electives can be taken. This can be done through the courses MTH321A Internship I, MTH322A Internship II, MTH323A Internship III, MTH324A Internship IV, MTH325A Internship V, of 9 credits each. One would have an option to earn 45 credits of OE through internship courses by spending a full semester in an industry or may do online internships (under one or more OEs) from industry, spread across different semesters. The process for enrolling in the internship courses is as follows: the student identifies a viable internship opportunity in the general realm of statistics and data science and identifies a supervisor in the MTH department. The student, in consultation with the host industry/organization submits a proposal to the Department Undergraduate Committee (DUGC) with the approval of the industry liaison and the departmental supervisor, upon which it will be evaluated for approval and requisite number of credits (in multiples of 9) will be decided. The grading scheme for the internship courses will be S/X.
Note: Guidelines for internships are available in this page.
Credit table for BS program in Statistics and Data Science | |
Course type | Credits in the department template |
Institute Core (IC) | 112 |
E/SO | 38 |
Department requirements | 154 (109 DC + 45 DE) |
Open electives (OE) | 54 |
SCHEME | 54-58 |
Total for 4-year BT/BS | 412-416 |