Lecture - Artificial Intelligence

Artificial Intelligence (AI) is transforming nearly every aspect of modern society - from healthcare, cybersecurity, and transportation to finance, robotics, and intelligent decision support systems. As AI technologies continue to evolve, there is a growing need for professionals who understand both the theoretical foundations and practical applications of intelligent systems.

This course introduces the fundamental concepts, methods, and techniques of AI. Students will learn how intelligent agents reason, search, learn, and make decisions in complex and uncertain environments.

 

Learning objectives. By the end of the course, students will be able to:

  • Understand the core principles of AI
  • Analyze and design search and decision-making algorithms
  • Model and solve optimization and planning problems
  • Apply AI methods in uncertain and adversarial environments
  • Understand the foundations of reinforcement learning and sequential decision making

 

Course content:

(Topics may be adjusted slightly during the semester)

  • Intelligent Agents
  • Uninformed Search
  • Informed/ Heuristic Search
  • Constraint Satisfaction Problems (CSPs)
  • Adversarial Search and Games
  • Markov Decision Processes (MDPs)
  • Reinforcement Learning (RL)
  • Local Search and Optimization

 

Literature: