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Due to the exceptional circumstances caused by the COVID-19 pandemic, the learning activities, assessments and attendance requirements for this unit may be subject to late changes. Please refer to this unit outline regularly for up to date information and to notices in the unit’s Canvas site for any adjustments.

Unit of study_

COMP3608: Introduction to Artificial Intelligence (Adv)

An advanced alternative to COMP3308; covers material at an advanced and challenging level.

Code COMP3608
Academic unit Computer Science
Credit points 6
Prerequisites:
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Distinction-level results in at least one 2000 level COMP or MATH or SOFT unit
Corequisites:
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None
Prohibitions:
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COMP3308
Assumed knowledge:
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Algorithms. Programming skills (e.g. Java, Python, C, C++, Matlab)

At the completion of this unit, you should be able to:

  • LO1. Formulate problem space description, select and apply suitable search algorithms and analyse the issues involved
  • LO2. Understand and apply minimax search and alpha-beta pruning in game playing
  • LO3. Understand the basic principles and analyse the strengths, weaknesses and applicability of some of the main AI algorithms for supervised learning, unsupervised learning and probabilistic reasoning
  • LO4. Gain practical experience in designing, implementing and evaluating AI algorithms
  • LO5. Present and interpret data and information in verbal and written form
  • LO6. Appreciate some of the main ideas and views in AI, achievements and shortcomings of AI and the links between AI and other Computer Science areas

Unit outlines

Unit outlines will be available 2 weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.

There are no unit outlines available online for previous years.