Artificial Intelligence (COMP30024)

Undergraduate level 3Points: 12.5On Campus (Parkville)

You’re viewing the 2025 Handbook:
Or view archived Handbooks

Overview

Availability
Semester 1
FeesLook up fees

AIMS

Artificial intelligence is the quest to create intelligent agents that can complete complex tasks which are at present only achievable by humans. This broad field covers logic, probability, perception, reasoning, learning and action; and everything from Mars Rover robotic explorers to the Watson Jeopardy playing program. You will explore some of the vast area of artificial intelligence. Topics covered include: searching, problem solving, reasoning, knowledge representation and machine learning. Topics may also include some of the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics and agent-based systems.

 

INDICATIVE CONTENT

  • Agents and search
  • Probabilistic reasoning
  • Reinforcement Learning
  • Pattern recognition for robotics.

Intended learning outcomes

On completion of this subject the student is expected to:

  • Identify problems that can be solved by search, and create search-based solution algorithms
  • Design intelligent agents
  • Choose the best search-based solving methods for a particular problem
  • Make use of formal approaches for representing and reasoning about knowledge
  • Build systems that use simple learning approaches to improve their performance

Generic skills

On completion of this subject students should have developed the following generic skills:

  • The ability to analyse and solve problems involving complex reasoning
  • The ability to synthesise information and communicate results effectively
  • The capacity for critical and independent thought and reflection
  • The ability to apply knowledge of basic science and engineering fundamentals
  • The ability to undertake problem identification, formulation and solution.

Last updated: 4 April 2025

Eligibility and requirements

Prerequisites

Prerequisites

One of

Code Name Teaching period Credit Points
COMP20003 Algorithms and Data Structures
Semester 2 (On Campus - Parkville)
 12.5
COMP20007 Design of Algorithms
Semester 1 (On Campus - Parkville)
 12.5

OR

Admission into or selection of one of the following:

  • GC-CS Graduate Certificate in Computer Science
  • MC-SOFTENG Master of Software Engineering

Corequisites

None

Non-allowed subjects

433-303 Artificial Intelligence

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 4 April 2025

Assessment

DescriptionTimingPercentage

A programming project submitted in two parts during semester. A component of the marks for the project work will be based on the individual contribution to the project.

  • 30-35 hours (of work required)
Hurdle requirement: Please see below		During the teaching period30%

Written examination

  • 3 hours
Hurdle requirement: Please see below		End of semester70%

Additional details

Hurdle requirement: To pass the subject, students must obtain at least 50% overall

  • 15/30 in project work
  • And 35/70 in the written examination.

Intended Learning Outcomes (ILOs) 1-4 are addressed in the lectures, workshops exercises and the examination.

ILO 5 is addressed in the project work.

Last updated: 4 April 2025

Dates & times

  • Semester 1
    Principal coordinatorChristopher Leckie
    Mode of deliveryOn Campus (Parkville)
    Contact hours36 hours, comprising of two 1-hour lectures and one 1-hour tutorial per week
    Total time commitment170 hours
    Teaching period 3 March 2025 to 1 June 2025
    Last self-enrol date14 March 2025
    Census date31 March 2025
    Last date to withdraw without fail 9 May 2025
    Assessment period ends27 June 2025

    Semester 1 contact information

    Email: caleckie@unimelb.edu.au 

Time commitment details

170 hours

What do these dates mean

Visit this webpage to find out about these key dates, including how they impact on:

  • Your tuition fees, academic transcript and statements.
  • And for Commonwealth Supported students, your:
       -  Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
     

    Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.

Last updated: 4 April 2025

Further information

Last updated: 4 April 2025