This module provides the student with an understanding of state-of-the-art data analysis concepts and techniques, and the ability to develop solutions to big data problems using suitable algorithms and software.
Data Analysis, Theory and Methods
Data Collection, Sampling, Descriptive statistics, Inferential statistics
Data Theory, Concepts and Methods
Data bias, handling missing data, investigating outliers and erroneous data, data generation techniques.Effects of data bias.
Data Analysis & Scripting
Reading Data; Cleaning and Filtering Data; Data Pre-processing and attribute techniques for ML algorithms.Visualisation of Data
Public Cloud Solutions
Developing solutions using Public Cloud Providers, using analysis tools (eg Jupyter notebooks) with access to HPC architectures.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 100 |