Module Learning Outcomes
Module Content
Specific topics addressed in this module include:
- A further look a machine learning methods, building on the work in STP80080.
- An introduction to distributed computing and how it is used in data science;
- Security and privacy issues with data;
- Industry case study.
Teaching and learning Methods
This module is online with 4 weekly sessions. All content is available through Blackboard. Live online tutorials with the module lecturer or teaching demonstrator will be given.
Assessment Details
Reassessment Details
100% supplemental open book take home examination
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 33 hours |
| Lecture | 33 |
| Independent study (outside scheduled contact hours), broken down by: | 82 hours |
| Preparation for classes and review of material (including preparation for examination, if applicable | 42 |
| completion of assessments (including examination, if applicable) | 40 |
| Total Hours | 115 hours |
| |
Module Pre-requisites
STP80080 Foundations of Data Science 1
Module Co-requisites
None
Module Website
Blackboard