M.Tech. in Computational and Data Science
Source: https://cds.iisc.ac.in/academics/mtechcds/ Parent: http://cds.iisc.ac.in/admissions/course-degrees/
M.Tech. in Computational and Data Science
Course structure: (effective from Aug 2018 batch)
- Hard Core: 14 credits
- Courses: 13 credits
- Research Methods: 1 credit (soft skills course)
- Soft Core: 10 credits minimum (atleast three courses)
- Dissertation: 28 credits
- Electives: 12 credits (Students may credit CDS electives/soft core or other department courses)
Total: 64 credits
Hard Core Courses (14 credits): All are compulsory
- DS 215 AUG 3:0 Introduction to Data Science (AC)
- DS 221 AUG 3:1 Introduction to Scalable Systems (VSS/YS)
- DS 284 AUG 2:1 Numerical Linear Algebra (PM)
- DS 288 AUG 3:0 Numerical Methods (RB)
- DS 200 AUG 0:1 Research Methods (DP) – SOFT SKILLS COURSE [to be taken in the second year August term]
Soft Core Courses (10 credits): Minimum three courses out of ten below
- DS 201 AUG 2:0 Bioinformatics (KS/DP)
- DS 202 JAN 2:1 Algorithmic Foundations of Big Data Biology (CJ)
- DS 211 AUG 3:0 Numerical Optimization (DS)
- DS 216 JAN 3:1 Machine learning for Data Science (VS)
- DS 207 JAN 3:1 Introduction to Natural Language Processing (DAP)
- DS 226 AUG 2:1 Introduction to Computing for AI & Machine Learning (SG)
- DS 256 JAN 3:1 Scalable Systems for Data Science (YS)
- DS 285 JAN 3:1 Tensor Computations for Data Science (RB)
- DS 289 JAN 3:1 Numerical Solution of Differential Equations (KA)
- DS 290 AUG 3:0 Modelling and Simulation (SR)
- DS 295 JAN 3:1 Parallel Programming (SV)
- DS 298 JAN 3:0 Random Variates in Computation (MV)
- E0 261 JAN 3:1 Database Management Systems (JH)
Dissertation Project:DS 299 0:28 (0:4 Summer; 0:8 AUG; 0:16 JAN)
*CDS Electives (all existing electives) / Elective courses offered by CDS Faculty. Check here for the FULL LIST of COURSES*
- DS 244 JAN 2:1 Hardware-aware Scientific Computing (SG)
- DS 255 JAN 3:1 System Virtualization (JL)
- DS 261 AUG 2:1 Artificial Intelligence for Medical Image Analysis (PY)
- DS 263 AUG 3:1 Video Analytics (RVB/AC)
- DS 265 JAN 3:1 Deep Learning for Computer Vision (RVB)
- DS 269 JAN 2:1 Computational Methods for Reacting Flows (AK)
- DS 392 JAN 3:1 Environmental Data Analytics (DS)
- DS 393 JAN 3:1 High-performance Computing for Quantum Modeling of Materials (PM)
- DS 397 JAN 2:1 Topics in Embedded Computing
- E0 361 AUG 3:1 Topics in Database Systems (JH)