The following courses are required for a minor in Statistics and Data Science.
- MSO 205 (Introduction to Probability theory) or MSO 201 (Probability and Statistics) or HSO 201 (Applied probability and statistics) or CS 203 (Mathematics for Computer Science - III)
- MTH 211 (Theory of Statistics)
- MTH 208 (Data Science Lab 1)
- MTH 441 (Linear regression and ANOVA)
| I Semester | II Semester | ||||
| IC: MTH 101A Mathematics I |
3-1-0-0 | 11 | IC: MTH 102A Mathematics II |
3-1-0-0 | 11 |
| IC: PHY 103A Physics II |
3-1-0-0 | 11 | IC: PHY 102A Physics I |
3-1-0-0 | 11 |
| IC: CHM 101A Chemistry Laboratory |
0-0-3-0 | 03 | IC: PHY 101A Physics Laboratory |
0-0-3-0 | 03 |
| IC: ESC 101A Fundamental of Computing |
3-1-3-0 | 14 | IC: LIF 101A Introduction to Biology |
2-0-0-0 | 06 |
| HSS: ENG 112A/HSS-1 (Level-1) | 3-1-0-0 | 11 | IC: CHM 102A General Chemistry |
2-1-0-0 | 08 |
| IC:PE 101A Morning Exercise |
0-0-3-0 | 03 | IC: PE 102A Evening Exercise |
0-0-3-0 | 03 |
| IC: TA 101A Engineering Graphics |
2-0-3-0 | 09 | |||
| Total | 53 | Total | 51 | ||
| III Semester | IV Semester | ||||
| DC: MTH 301A Analysis I |
3-1-0-0 | 11 | DC: MTH 211A Theory of Statistics |
3-1-0-0 | 11 |
| ESO/SO-1: MSO 205A Introduction to Probability Theory |
3-1-0-0 | 11 | DC: MTH 210A Statistical Computing |
3-0-1-0 | 10 |
| ESO/SO-2: MSO 202A Introduction to Complex Analysis (Modular I) |
3-1-0-0 | 06 | DC: MTH 212A Elementary Stochastic Processes I (Modular I) |
3-1-0-0 | 06 |
| DC: MTH 207A Matrix Theory and Linear Estimation (Modular II) |
3-1-0-0 | 06 | DC: MTH 209A Data Science Lab 2 |
1-0-2-0 | 05 |
| DC: MTH 208A Data Science Lab 1 |
0-0-3-2 | 05 | HSS: HSS-2 (Level-1) | 3-1-0-0 | 11 |
| IC: ESC 201A Introduction to Electronics |
3-1-3-0 | 14 | IC: TA 202A Manufacturing Process II |
1-0-3-0 | 06 |
| IC: TA 201A Manufacturing Process I |
1-0-3-0 | 06 | ESO/SO-3: | 3-0-0-0 | 09 |
| Total | 59 | Total | 58 | ||
| V Semester | VI Semester | ||||
| DC: MTH 442A Time Series Analysis |
3-0-1-0 | 10 | DC: MTH 422A Bayesian Analysis |
3-0-1-0 | 10 |
| DC: MTH 441A Linear Regression and ANOVA |
3-0-1-0 | 10 | DC: MTH 314A Multivariate Analysis |
3-0-1-0 | 10 |
| DC: MTH 399A Communication Skills |
0-0-2-0 | 02 | DC: MTH 312A Data Science Lab 3 |
1-0-2-0 | 05 |
| ESO/SO-4: ESO 207A Data Structures and Algorithms |
3-0-3-0 | 12 | ESO/SO-5: | 3-0-0-0 | 09 |
| IC: Com 200 Communication Skills: Composition |
1-1-0-0 | 05 | HSS: HSS-4 (Level-2) | 3-0-0-0 | 09 |
| HSS: HSS-3 (Level-2) | 3-0-0-0 | 09 | OE-2/UGP - 2 | 0-0-9-0 | 09 |
| OE-1: | 3-0-0-0 | 09 | |||
| UGP -1 (Extra Credit) | 0-0-4-0 | 04 | |||
| Total | 57/61 | Total | 52 | ||
| VII Semester | VIII Semester | ||||
| DC: MTH 443A Statistical and AI Techniques in Data Mining |
3-0-1-0 | 10 | DE – 3 | 09 | |
| DE - 1 | 09 | DE – 4 | 09 | ||
| DE - 2 | 09 | OE – 6 | 09 | ||
| OE – 3/UGP-3 | 09 | OE – 7 | 09 | ||
| OE – 4 | 09 | HSS: HSS-5 (Level-2) | 09 | ||
| OE - 5 | 09 | UGP4 (Extra Credit) | 09 | ||
| Total | 55 | Total | 45/54 | ||
Minimum credit requirement for graduation
| Bracket | Credits | Percentage |
| Institute Core (IC) | 124 | 28.8 |
| Department Compulsory (DC) | 111 | 25.8 |
| Department Elective (DE) | 36 | 8.4 |
| Open elective / UGP (OE / UGP) | 63 | 14.7 |
| ESO/SO | 47 | 10.9 |
| HSS | 49 | 11.4 |
| Total | 430 |
**Up to 45 credits of internships in lieu of open electives can be taken. This can be done through the courses MTH321 Internship I, MTH322 Internship II, MTH323 Internship III, MTH324 Internship IV, MTH325 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.
| 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 4th 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 |
| BS-MS PG (Part – Category A) (from the same department) | |||||
| COURSES | |||||
| IX Semester | X Semester | ||||
| MS Project – (PGP 1, PGP 2) | 6-0-0-0 | 18 | MS Project – (PGP 3, PGP 4) | 6-0-0-0 | 18 |
| DE PG - I | 3-0-0-0 | 09 | DE PG-II | 3-0-0-0 | 09 |
| OE PG - I | 3-0-0-0 | 09 | OE PG-III | 3-0-0-0 | 09 |
| OE PG - II | 3-0-0-0 | 09 | OE PG - IV | 3-0-0-0 | 09 |
| Total | 45 | 45 | |||
Minimum credit requirement in MS part for graduation
| Bracket | Credits |
| PG Component | 90 |
| Total | 90 |
Note: A maximum of 36 OE credits may be waived from the department under graduation requirement to be used for the PG requirement of dual degree students.
| BS-MS PG (Part – Category B) (from other departments) | |||||
| UG Pre-Requisites | |||||
| Odd Semester | Even Semester | ||||
| MTH 301A | 3-1-0-0 | 11 | MTH 211A | 3-1-0-0 | 11 |
| MTH 210A | 3-0-1-0 | 10 | |||
| MTH 207A | 3-1-0-0 | 06 | MTH 212A | 3-1-0-0 | 06 |
| MTH 442A | 3-0-1-0 | 10 | MTH 422A | 3-0-1-0 | 10 |
| MTH 441A | 3-0-1-0 | 10 | MTH 314A | 3-0-1-0 | 10 |
| MTH 443A | 3-0-1-0 | 10 | MTH 209A | 1-0-2-0 | 05 |
| MTH 208A | 0-0-3-2 | 05 | MTH 312A | 1-0-2-0 | 05 |
| Total | 52 | 57 | |||
| PG Requirement | |||||
| Odd Semester | Even Semester | ||||
| MS Project – (PGP 1, PGP 2) | 6-0-0-0 | 18 | MS Project – (PGP 3, PGP 4) | 6-0-0-0 | 18 |
| DE PG - I | 3-0-0-0 | 09 | DE PG-II | 3-0-0-0 | 09 |
| OE PG - I | 3-0-0-0 | 09 | OE PG-III | 3-0-0-0 | 09 |
| OE PG - II | 3-0-0-0 | 09 | OE PG - IV | 3-0-0-0 | 09 |
| Total | 45 | 45 | |||
Note: A maximum of 36 OE credits may be waived from the parent department graduation requirement to be used for the PG requirement of dual degree students.