Course overview
This is an introductory course on Artificial Intelligence. The topics may include: AI methodology and fundamentals; intelligent agents; search algorithms; game playing; machine learning; uncertainty and probability theory; probabilistic reasoning in AI; Bayesian networks; decision making, and reinforcement learning. Several assignments will be given to enable the student to gain practical experience in using these techniques.
Course learning outcomes
- Explain what constitutes "Artificial" Intelligence and how to identify systems with Artificial Intelligence
- Explain how Artificial Intelligence enables capabilities that are beyond conventional technology, for example, chess-playing computers, self-driving cars, robotic vacuum cleaners
- Use classical Artificial Intelligence techniques, such as search algorithms, minimax algorithm, neural networks, tracking, robot localisation
- Ability to apply Artificial Intelligence techniques for problem solving
- Explain the limitations of current Artificial Intelligence techniques