semester 4 computer science courses at IISc
| course name | course details | course artifact | course grade |
|---|---|---|---|
| Introduction to Artificial Intelligence and Machine Learning (UMC 203) | Overview: Machine Learning paradigms; supervised, unsupervised, and reinforcement learning. Supervised Learning : Bayes classifier, optimality; risk minimization; Generalisation error estimation. Perceptron, logistic regression, least squares, regularization, Kernel methods; SVMs, multilayer Perceptrons, CNNs, and other neural network models. Classifier ensembles, Adaboost algorithm. Unsupervised Learning: Generative models, parameter estimation – Maximum likelihood, Bayesian Methods; latent variables and EM algorithm; graphical models, deep generative models, Principal component Analysis, Independent Component Analysis. Reinforcement Learning and Markov Decision Processes. |
Assignment 1
Assignment 2 |
A+ |
| Reinforcement Learning (E1 277) | Introduction to reinforcement learning, introduction to stochastic dynamic programming, finite and infinite horizon models, the dynamic programming algorithm, infinite horizon discounted cost and average cost problems, numerical solution methodologies, full state representations, function approximation techniques, approximate dynamic programming, partially observable Markov decision processes, Q-learning, temporal difference learning, actor-critic algorithms. | A | |
| Automata Theory and Computability (UMC 205) | Finite-state automata: deterministic finite-state automata, pumping lemma, non-deterministc automata, regular expressions, Myhill-Nerode theorem, and ultimate periodicity. Pushdown automata and context-free languages: context-free grammars, Chomsky normal form, pumping lemma for CFLs, Parikh’s semilinearity theorem, non-deterministic pushdown automata, equivalence of context-free grammars and pushdown automata, pushdown systems and reachability, and complementing deterministic PDA’s. Turing machines and undecidability: deterministic Turing machines, notion of computable functions using Turing machines, recursive and recursively enumerable languages, halting problem, reductions, Rice’s theorems, undecidable problems related to context-free languages, and Godel’s Incompleteness theorem. | B |