Artificial Intelligence Tutorial

1. AI Introduction

What artificial intelligence means, how AI, machine learning, deep learning and LLMs relate, and a brief history of the field.

2. History & Timeline of AI

From symbolic AI and expert systems through statistical ML, deep learning and transformers — real dates and milestones.

3. Problem Types & Approaches

Classification, regression, clustering and generation; rule-based vs learned approaches; and where classical algorithms still win.

4. Search & Planning

State-space search, A* pathfinding, and minimax/game trees for adversarial games, with worked examples.

5. AI Ethics & Bias

How bias enters training data, fairness trade-offs, and real documented failures like COMPAS and the Amazon hiring tool.

6. AI Interview Questions

Commonly asked AI fundamentals interview questions with clear, practical answers.