Artificial Intelligence (UoA)

Undergraduate | 2026

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Area/Catalogue
COMP 3027
Course ID icon
Course ID
205800
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
3
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

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

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A