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
Availability
Class details
Adelaide City Campus East
Class number 24069
Section LE01
Size 250
Available 250
Class number 26162
Section WS01
Size 30
Available 30
Class number 26161
Section WS02
Size 30
Available 30
Class number 26160
Section WS03
Size 30
Available 30
Class number 26159
Section WS04
Size 30
Available 30
Class number 26158
Section WS05
Size 30
Available 30
Class number 26157
Section WS06
Size 30
Available 30
Class number 26156
Section WS07
Size 30
Available 30
Class number 26155
Section WS08
Size 30
Available 30
Class number 27159
Section WS09
Size 30
Available 30
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