Module overview
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Gain facility in working with algorithms to handle data sets in a scientific computing environment
- Systematically work with data to learn new patterns or concepts
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Underlying mathematical principles from probability, linear algebra and optimisation
- The relationship between machine learning and biological learning
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Gain a broad understanding of the latest research issues
- Use data to reinforce one/few among many competing explanatory hypotheses
- Characterise data in terms of explanatory models
Syllabus
Learning and Teaching
Teaching and learning methods
Type | Hours |
---|---|
Supervised time in studio/workshop | 6 |
Lecture | 20 |
Follow-up work | 10 |
Revision | 10 |
Wider reading or practice | 76 |
Completion of assessment task | 18 |
Preparation for scheduled sessions | 10 |
Total study time | 150 |
Resources & Reading list
Textbooks
Simon Rogers and Mark Girolami (2016). A First Course in Machine Learning. Chapman and Hall/CRC.
Mackay, David J. C.. Information Theory, Inference and Learning Algorithms..
Bishop, Christopher M.. Pattern Recognition and Machine Learning.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Examination | 80% |
Coursework | 20% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Examination | 100% |
Repeat Information
Repeat type: Internal & External