An Artificial Intelligence (AI) course explores how to build systems capable of perceiving their environment, reasoning through complex scenarios, and taking goal-oriented actions. It begins with classical AI, covering deterministic and adversarial search algorithms like A* Search and Minimax for pathfinding and game-playing, alongside formal logic and Bayesian Networks for handling real-world uncertainty. The curriculum then shifts heavily into modern Machine Learning, teaching agents to extract patterns from data via supervised, unsupervised, and reinforcement learning paradigms. This culminates in Deep Learning, where students study artificial neural networks, including Convolutional Neural Networks (CNNs) for computer vision and Transformers for Natural Language Processing (NLP). Finally, the course addresses critical philosophical and ethical dimensions, emphasizing data bias, the alignment problem, and safety to ensure intelligent systems behave beneficially.
- Teacher: Valens Nsengiyumva