| MODULE 1: Introduction to Robotics and Expert System |
| Introduction to Robotics, Components of a Robot, Robot Locomotion, Types of Robots, Classification of Robots, characteristics of Robot, Introduction to Expert System, Forward Chaining, Backward Chaining, Decision Support System, Types of Agents, Intelligent Agent, Agent Environment, End Effectors and Kinematics | |
| MODULE 2: Computing, Measurement, State, and Parameter Estimation |
| Sensors and Sensing Formal and Fuzzy Logic Turing Machines and Concepts of Machine Learning Analog and Digital Systems | |
| MODULE 3: Decision-Making and Machine Learning |
| Decision Trees Bayesian Belief Networks Classification and data sets | |
| MODULE 4: Neural Networks for Classification and Control |
| Feed-Forward Networks Back propagation Networks Associative Networks Deep-Learning Algorithms | |
| MODULE 5: Numerical Methods for Evaluation and Search |
| Agents in Artificial Intelligence Monte Carlo Simulation Genetic Algorithms Particle Swarm Optimization | |