Mathematics

Data Science Research Methods (L6)

Module code: G5222
Level 6
15 credits in autumn semester
Teaching method: Lecture, Laboratory
Assessment modes: Coursework

This module will provide students with the practical tools and techniques required to complete the Data Science Process: data pre-processing, exploratory data analysis, communication and visualisation, mathematical modelling, and the development of a data solution or product. To do this, students will get to develop their programming skills and be introduced to some fundamental data science packages/libraries. As well as learning about standard methodologies for data processing and exploring, students will be introduced to some advanced mathematical tools and techniques data scientists use in their day-to-day lives, such as regression models, classification, and clustering. In practical sessions, students will be able to apply these tools and techniques to real-world datasets.

Module learning outcomes

• Analyse and explore real-word datasets using appropriate tools and techniques.
• Systematically understand the context of when tools and techniques for data analysis can be applied in different scenarios.
• Apply, evaluate, and interpret tools and techniques for data analysis and visualisation in different scenarios.
• Produce an analysis of datasets and apply data visualisation tools and techniques to present data and analyses in an appropriate format.