Artificial Intelligence and Statistics

Course content

Foundations and history of Artificial Intelligence (AI). Logical programming. Problem solving. Searching. Game playing. Knowledge, reasoning, planning. Theorem proving. Uncertain knowledge and probabilistic reasoning. Hidden Markov Models. Kalman filters. Bayesian networks. Belief networks. Machine learning. Statistical learning. Reinforcement learning. Natural Language Processing (NLP). Pattern recognition. Speech and image processing. Future of AI. Robotics.