Faculty of Information Technology

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This unit entry is for students who completed this unit in 2016 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

Monash University

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.


Information Technology



  • Second semester 2016 (Day)


  • Second semester 2016 (Day)


This unit includes history of artificial intelligence; intelligent agents; problem solving and search (problem representation, heuristic search, iterative improvement, game playing); knowledge representation and reasoning (extension of material on propositional and first-order logic for artificial intelligence applications, planning, frames and semantic networks); reasoning under uncertainty (belief networks); machine learning (decision trees, Naive Bayes, neural nets and genetic algorithms); language technology.


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

  1. describe the historical and conceptual development of AI; foundational issues for AI, including the frame problem and the Turing test;
  2. explain, apply and evaluate the goals of AI and the main paradigms for achieving them including logical inference, search, machine learning and Bayesian inference;
  3. explain the social and economic roles of AI;
  4. describe, analyse, apply and evaluate heuristic AI for problem solving;
  5. describe, analyse and apply basic knowledge representation and reasoning mechanisms;
  6. describe, analyse and apply probabilistic inference mechanisms for reasoning under uncertainty;
  7. describe, analyse, apply and evaluate machine learning techniques;
  8. describe, analyse, apply and evaluate the use of the above techniques in different domain, specifically language technology.


Examination (3 hours): 60%; In-semester assessment: 40%

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • Two hours of lectures
  • One 1-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 9 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Chief examiner(s)

This unit applies to the following area(s) of study

Advance computer science


FIT2004 or CSE2304


CSE2309, CSE3309, DGS3691

Additional information on this unit is available from the faculty at: