Module 06-32258 (2022)
Algorithms for Data Science
Level 4/M C
|Peter Tino Miqing Li||Semester 1||20 credits|
Modern data science encompasses a huge range of methods – from supervised methods for learning from labelled data, to statistical pattern analysis and data mining. In this module students will study a range of modern techniques from across the data science spectrum including supervised learning, data mining, and statistical pattern recognition. The module will give the student a good understanding of how, why and when different methods work and experience of applying them in practice.
On successful completion of this module, the student should be able to:
- Understand and explain a range of methods and algorithms for data science
- Be able to apply a range of algorithms to solve data science problems
- Compare and contrast different methods, analysing their relative advantages and disadvantages
- Make informed choices between different methods, given a data science question, and be able to justify these choices.
- Main Assessments: Examination (80%) and continuous assessment (20%)
- Supplementary Assessments: Examination (100%)
Programmes containing this module
- MSc Data Science [472D]