AI

• Week1(2nd Feb)

  • Introduction 

• Week2(9th Feb)

  • AI Types & Classification

• Week3(16th Feb)

  • AI Agents

• Week4(23rd Feb)

  • AI Agents Implementation

  • Problem Solving

• Week5(2nd March)

  • Problem Solving - Uninformed Search

• Online Sessions

  • Problem Solving - Informed Search (26 March)

  • Local Search (27 March)

• Week (1st April)

  • Learning-Introduction

• Week (6th April)

  • Learning -Continued

  • AIS Installation

• Week (13th April)

  • Lab Implementation - Exemplary Model

  • Mid

  • how to design a learning model.

• After Mid

  • Learning-Supervised

  • Learning-Evaluation

  • Learning-Unsupervised

  • KR & Reasoning

  • FOL

  • KB lab

Implementations:

• AI Agent Implementation as per PEAS.

• Apply the Breadth-First Search (BFS) algorithm to determine the shortest path from NIPA to Mazar-e-Quaid. Identify all areas along the route and define their neighboring locations using a map.

• Apply the A* Search algorithm to determine the path from NIPA to Mazar-e-Quaid. Use an appropriate heuristic to guide the search. Identify all areas along the route, define their neighboring locations using a map, and show the calculation of g(n), h(n), and f(n) values at each step.

• Apply Learning Model to Kaggle dataset.

• Generate Dataset for a Player AI model.