On Campus Courses
Computational learning theory
Foundations of Data Science
Foundations of Deep Learning (Special Topics)
Applied Statistical Methods
Reading Courses
Functional Analysis in Activation Functions (Sem II 2020)
Approximation Algorithms (Sem I 2021)
Graph Algorithms (Sem II 2021)
Optimization for Deep Learning (Semester I 2022)
Deep Learning In Protein Folding (Sem II 2022)
Reinforcement Learning for the Last Mile Delivery Problem (Sem II 2023)
WILP Courses
Machine Learning (Sem II 2020)
Machine Learning (Sem II 2021)
Contribution to Curriculum Development
New Course-Computational Learning Theory(COLT)
Recorded 35 lectures on Machine Learning for WILP (Flipped Mode)
Redesigned WILP courses on Optimization, Computational intelligence
New Minor in Computational Economics
Some Lecture content are available here: https://scibasesnehanshu.wixsite.com/ieeecompsocblr/education
My Youtube Channel: https://www.youtube.com/playlist?list=PLMj0pXCZmlXhYD43yMvn54pFhbtWreUJb
Courses Taught (Previous Roles)
Computer Systems Performance Analysis
Discrete Mathematics
Advanced Algorithms
Randomized Algorithms
Stochastic Processes for Computing
Graph Theory
Logic in Computer Science
Scientific Computing
Probability Theory for Computer Science
Linear Algebra
Introduction to Data Analytics
Pattern Recognition