# CS3491: Artificial Intelligence and Machine Learning syllabus for ECE 2021 regulation

Artificial Intelligence and Machine Learning detailed syllabus for Electronics & Communication Engineering (ECE) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the ECE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Electronics & Communication Engineering 6th Sem scheme and its subjects, do visit ECE 6th Sem 2021 regulation scheme. The detailed syllabus of artificial intelligence and machine learning is as follows.

Artificial Intelligence and Machine Learning

#### Unit I

PROBLEM SOLVING 9Introduction to AI – AI Applications – Problem solving agents â€“ search algorithms â€“ uninformed search strategies â€“ Heuristic search strategies â€“ Local search and optimization problems â€“ adversarial search â€“ constraint satisfaction problems (CSP)

#### Unit III

SUPERVISED LEARNING 9Introduction to machine learning â€“ Linear Regression Models: Least squares, single & multiple variables, Bayesian linear regression, gradient descent, Linear Classification Models: Discriminant function â€“ Probabilistic discriminative model – Logistic regression, Probabilistic generative model â€“ Naive Bayes, Maximum margin classifier â€“ Support vector machine, Decision Tree, Random forests

#### Unit V

NEURAL NETWORKS 9Perceptron – Multilayer perceptron, activation functions, network training â€“ gradient descent optimization â€“ stochastic gradient descent, error backpropagation, from shallow networks to deep networks â€“Unit saturation (aka the vanishing gradient problem) â€“ ReLU, hyperparameter tuning, batch normalization, regularization, dropout.

#### Course Outcomes:

1. Use appropriate search algorithms for problem solving
2. Apply reasoning under uncertainty
3. Build supervised learning models
4. Build ensembling and unsupervised models
5. Build deep learning neural network models

#### Text Books:

1. Stuart Russell and Peter Norvig, ‘Artificial Intelligence â€“ A Modern Approach’, Fourth Edition, Pearson Education, 2021
2. Ethem Alpaydin, ‘Introduction to Machine Learning’, MIT Press, Fourth Edition, 2020