Data Science and Machine learning
This module aims to provide the fundamentals of data science and machine learning, with the goal of introducing data collection, extraction, and analysis to provide critical insights. The module aims to introduce students to a typical data analysis pipeline together with the necessary programming and theoretical background.
Principal Learning Outcomes
By the end of module students will be able to:
- Perform the critical tasks of obtaining, cleaning, and exploratory analysis of dataset
- Compare whether supervised learning is the only/best choice for analysing data, compared to classical statistical analysis
- Apply supervised/unsupervised learning algorithms by suitable programming languages and software suites.
- Describe limits and assumptions inherent to supervised/unsupervised learning from data.