ARTIFICIAL INTELLIGENCE (5 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: Describe what is AI and identify concept of intelligent agent; Explain various intelligent search algorithms to solve the problems; Explain how to use knowledge representation in reasoning purpose; Apply various techniques to an agent when acting under certainty; Apply various AI algorithms to solve the problems; Identify value propositions in business with physical / visual representation of an idea.

Topics:

Introduction to Prototype Development I; Introduction to Artificial Intelligence; Search Strategies; Local Search; Adversarial Search; Logical Agents; First Order Logic; VPC & Idea Profile; Fuzzy Systems; Quantifying Uncertainty 1; Quantifying Uncertainty 2; Probabilistic Reasoning; AI Application; Solution Sketch & Storyboard; AI Application; Probabilistic Reasoning Over Time; Project Proposal Presentation; Learning from Examples; Product/Service Prototype; Introduction to Machine Learning; Linear Regression & Classification; Products / Services Features & Function; Linear Regression & Classification; K-Nearest Neighbour; Support Vector Machine; Key Resources & Pitch Deck; Learning Probabilistic Models; Natural Language Processing; Natural Language for Communication; Introduction to Computer Vision; Report (Entrepreneurship); Project Proposal Presentation