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FIT3080 · Monash University

Artificial intelligence

Credit points
6
Level
3
Workload
≈ 12 h / week
Faculty
Information Technology

What it covers

This unit covers the history of artificial intelligence and the foundational concepts of intelligent agents. It delves into problem-solving and search techniques, including problem representation, heuristic search, and adversarial search. You will learn about knowledge representation and reasoning, focusing on propositional and first-order logic for AI applications, as well as planning. The unit also explores reasoning under uncertainty through Bayesian Networks and Markov Decision Processes. In the realm of machine learning, the unit includes reinforcement learning techniques, supervised learning such as decision trees, Naive Bayes, neural networks, and self-supervised learning approaches. Additionally, the unit addresses various AI applications and examines ethical considerations in AI

Assessment

TaskTypeWeight
ExaminationExamination50%
Assignment 1Artefact20%
Assignment 2Artefact10%
Assignment 3Artefact20%

When and where

Teaching periodCampusMode
Second semesterClaytonFlexible