FIT1059 · AI for everyone

Overview

This unit acts as a deep but non-mathematical entry point into the fascinating and fast-growing world of Artificial Intelligence (AI). It covers the early history of AI and its progress towards the current state of the art. AI’s fundamental concepts and techniques are introduced in common language, enabling you to successfully navigate the appropriate and ethical application of new technologies. We introduce topics such as intelligent agents, machine learning, deep learning and generative AI, to demonstrate AI’s key principles, strengths and limitations. AI’s implications and applications will be explored to assess their impact on individuals, organisations, industry, society and the environment. In these contexts, we will discuss the ethics and practice of AI’s use. Overall, this subject provides you opportunities to explore the latest developments in AI and gain hands-on experience in using AI tools. You will discuss and critically examine AI’s impacts, benefits and drawbacks. This unit is designed for students without a computer science background or programming experience. Students outside of the Faculty of IT are encouraged to enrol in this unit.

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

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Describe the key milestones in the development of AI technology.
2. Describe the key concepts in AI and machine learning.
3. Summarise the introductory knowledge to popular machine learning algorithms (e.g., symbolic, statistical approaches) and their advantages and disadvantages.
4. Explain deep learning (deep neural networks, transformers), how it works and where it can and cannot be applied.
5. Describe the use of AI in cognitive systems such as vision, language, speech or multimodal combination thereof.
6. Discuss bias, fairness, transparency and responsible use in AI systems.
7. Discuss use cases of AI as well as societal implications of AI.

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.