Mini Map

Symbolic artificial intelligence and machine learning

FIT2111

Synopsis

This unit covers the concepts of intelligent agents and 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. You will also engage with a variety of machine-learning techniques, including data representation, unsupervised and supervised learning and reinforcement learning. The curriculum also addresses the selection of appropriate model complexity tailored to specific problems and datasets. Through problem-based learning activities, you will apply these techniques to real-world scenarios and examine ethical considerations in AI.

Sourced from the Monash Handbook 2026.

Quick facts

Credit points
6
Level
2
Audience
Undergraduate
Type
Coursework
School
Faculty of Information Technology
Handbook year
2026

Prerequisites (2)

What it unlocks (3)

Listed in 1 area of study

  • Artificial intelligenceCore units