EEE

# OCS351: Artificial Intelligence and Machine Learning Fundamentals syllabus for EEE 2021 regulation (Open Elective-I)

Artificial Intelligence and Machine Learning Fundamentals detailed syllabus for Electrical & Electronics Engineering (EEE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the EEE 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 Electrical & Electronics Engineering 6th Sem scheme and its subjects, do visit EEE 6th Sem 2021 regulation scheme. For Open Elective-I scheme and its subjects refer to EEE Open Elective-I syllabus scheme. The detailed syllabus of artificial intelligence and machine learning fundamentals is as follows.

Artificial Intelligence and Machine Learning Fundamentals

#### Unit I

INTELLIGENT AGENT AND UNINFORMED SEARCH 6 Introduction – Foundations of AI – History of AI – The state of the art – Risks and Benefits of AI -Intelligent Agents – Nature of Environment – Structure of Agent – Problem Solving Agents -Formulating Problems – Uninformed Search – Breadth First Search – Dijkstra’s algorithm or uniformcost search – Depth First Search – Depth Limited Search

#### Unit III

LEARNING 6 Machine Learning: Definitions – Classification – Regression – approaches of machine learning models – Types of learning – Probability – Basics – Linear Algebra – Hypothesis space and inductive bias, Evaluation. Training and test sets, cross validation, Concept of over fitting, under fitting, Bias and Variance – Regression: Linear Regression – Logistic Regression

#### Unit V

UNSUPERVISED LEARNING 6 Unsupervised Learning – Principle Component Analysis – Neural Network: Fixed Weight Competitive Nets – Kohonen Self-Organizing Feature Maps – Clustering: Definition – Types of Clustering – Hierarchical clustering algorithms – k-means algorithm

#### Course Outcomes:

1. Understand the foundations of AI and the structure of Intelligent Agents
2. Use appropriate search algorithms for any AI problem
3. Study of learning methods
4. Solving problem using Supervised learning
5. Solving problem using Unsupervised learning

#### Text Books:

1. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Fourth Edition, 2021
2. S.N.Sivanandam and S.N.Deepa, Principles of soft computing-Wiley India.3 rd ed,