FIT1059 AI for everyone
Faculty of Information Technology
FIT1059 AI for everyone is a level 1, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2025 in Semester 2 at Clayton and Malaysia. It has no prerequisites.
- Credit points
- 6
- Offered in 2025
- Semester 2
- Clayton, Malaysia
- Assessment
- No exam
- 3 tasks
- Workload
- 144 hours
- per semester
This is the 2025 handbook entry. See the 2027 entry.
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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 students 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 students opportunities to explore the latest developments in AI and gain hands-on experience in using AI tools. Students 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 in 2025
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | Flexible |
| Second semester | Malaysia | On campus |
Assessment
- QuizzesQuiz / Test20%
- Project60%
- RoleplayDemonstration20%
Learning outcomes
When you finish this unit, you should be able to:
- 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 and teaching
- Seminars24 hours
- Applied sessions24 hours
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.
Contacts
- Chief Examiners
- Tien Tsin Wong
- Unit Coordinators
- Dr Ong Huey Fang
Common questions
What are the prerequisites for FIT1059?
FIT1059 has no prerequisites.
When is FIT1059 offered?
In 2025, FIT1059 runs in Semester 2 at Clayton and Malaysia.
How much work is FIT1059?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT1059 have an exam?
No. FIT1059 has 3 assessment tasks and no exam.