FIT1061 · Artificial intelligence algorithm foundations

Overview

This unit introduces you to the field of Artificial Intelligence (AI) as a specialisation within Computer Science. It provides an overview of the foundations of AI, including the history, key concepts, and applications across diverse domains such as language, vision, and intelligent decision-making. You will explore introductory AI problem-solving techniques and develop a basic understanding of how AI systems are designed to emulate aspects of intelligence. In parallel, the unit equips you with the essential mathematical and computational foundations required for later AI units. These include fundamental concepts from linear algebra and vector calculus, introduced in the context of solving simple AI-related problems such as classification and optimisation. Practical labs emphasise hands-on engagement through simulations, mathematical reasoning, and basic AI model-building, along with reflection on the societal and ethical implications of AI technologies.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Explain foundational artificial intelligence concepts, applications and system behaviours using appropriate computational terminology and representations;
2. Use introductory artificial intelligence methods and tools to explore search, classification, optimisation and model-building tasks in guided computational contexts;
3. Apply artificial intelligence engineering concepts to design, configure and evaluate introductory artificial intelligence workflows, models or system components for defined tasks;
4. Explain ethical, privacy and security considerations that arise in the design and use of artificial intelligence systems, including risks associated with data, models, outputs and deployment contexts;
5. Reflect on how artificial intelligence technologies can be designed, evaluated and applied to support equitable, responsible and environmentally aware outcomes for people, communities and society.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

Student experience, not official rules. Nothing here changes what the Handbook says.