Programme Overview
This programme explores the concepts, methods and practical questions involved in building and evaluating intelligent computational systems. The curriculum examines programming, machine learning, data, reasoning, language technologies and ethics, linking conceptual study with current questions in responsible development and use of intelligent tools.
You will work with computational problems and data-driven examples to understand how models are selected, evaluated and communicated. You will work through guided activities, applied scenarios and peer discussion, developing a disciplined approach to evidence, communication and independent work.
Ethics, transparency and human oversight are integrated throughout, helping you assess both the possibilities and limitations of artificial intelligence. Learning is organised for online participation, with clear milestones, tutor feedback and space to connect ideas across the programme. Throughout, opportunities to compare perspectives and receive formative feedback help consolidate your understanding, refine your judgement and prepare you to engage confidently with unfamiliar professional challenges. The final stage invites you to bring your learning together in a sustained piece of work.
What You’ll Learn
- Explain central concepts in artificial intelligence
- Implement foundational machine learning techniques
- Prepare and evaluate data for model development
- Compare approaches to search, reasoning and prediction
- Assess fairness, transparency and risk in AI systems
- Communicate technical findings to non-specialist audiences
Programme Structure
Level 4
- Programming Fundamentals
- Computing Mathematics
- Data and Information Fundamentals
- Introduction to Artificial Intelligence
- Academic Practice for Computing
Level 5
- Data Structures and Algorithms
- Machine Learning Fundamentals
- Database Systems
- Statistical Methods for AI
- Human-Centred AI
Level 6
- Deep Learning Concepts
- Natural Language Processing Fundamentals
- AI Systems Design
- AI Ethics and Governance
- Artificial Intelligence Project
Entry Requirements
Applicants are normally expected to have completed secondary education or an equivalent qualification. A basic grounding in mathematics or computing is helpful for this programme. Relevant work experience and prior learning may also be considered.
Applicants should be able to demonstrate English-language proficiency appropriate for degree-level study. Equivalent evidence of English proficiency may be considered as part of the application.
Assessment
Assessment may include technical exercises, practical coursework, reports, designs, demonstrations, portfolio work, presentations and a substantial final project. Examination-style assessments may be used where they provide a suitable way to assess underlying concepts and analytical reasoning.
Career Opportunities
- Junior AI Developer
- Machine Learning Assistant
- Data Analyst
- AI Product Analyst
- Automation Analyst
- Technology Research Assistant
Further Study
Graduates may pursue advanced study in artificial intelligence, machine learning, data science, robotics, computer science or responsible technology governance.