(Award available for year: Postgraduate Certificate)
Upon successful completion of the programme, students will be able to:
1. Demonstrate understanding of the foundational principles of programming, mathematics, and ethics that underpin artificial intelligence.
2. Apply fundamental machine learning techniques for classification, regression, and clustering to analyse and interpret data.
3. Explain how mathematical reasoning and algorithmic design enable machines to learn patterns and make predictions from data.
4. Develop and document reproducible code and workflows for basic data processing and exploratory analysis.
5. Evaluate model outputs and discuss issues of performance, bias, and fairness in the context of applied AI.
6. Reflect critically on the ethical, professional, and societal considerations associated with the design and use of AI systems.
Upon successful completion of the programme, students will be able to:
1. Apply logical and analytical reasoning to structure and solve defined problems in programming, mathematics, and foundational machine learning.
2. Demonstrate adaptability and independent learning by acquiring and applying new programming tools or analytical methods as needed.
3. Communicate technical ideas and analytical results clearly and appropriately using written, visual, and oral forms.
4. Apply analytical and structured reasoning to identify and address well-defined computational or ethical problems in AI.
5. Exercise reflective thinking to evaluate personal learning, identify areas for improvement, and develop confidence in technical problem solving.
6. Plan and manage learning activities and workflows systematically to meet project or assessment deadlines.
We will generally follow a combination of formative and summative assessments. The summative assessments take usually the form of:
1. One Test assessment in the middle of the module with relatively lighter weight between 20-40%
2. Final Project Assessment at the end of the module with a higher weight of 80-60%.
Errors, omissions, failed links etc should be notified to the Catalogue Team