Module overview
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- use appropriate techniques to obtain data from the web in an ethical manner;
- manage and extract information from unstructured data.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- analysing structured and unstructured data in a variety of formats.
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- select and apply methods for the analysis of textual data in Python, and interpret your results.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- write technical reports that present results in a clear and reproducible manner.
Syllabus
Learning and Teaching
Teaching and learning methods
| Type | Hours |
|---|---|
| Independent Study | 120 |
| Teaching | 30 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Toby Segaran (2007). Programming Collective Intelligence. Sebastopol, US: O'Reilly.
Han, Jiawei; Kamber, Micheline; Pei, Jian (2012). Data Mining. Waltham, MA, USA: Elsevier.
Assessment
Assessment strategy
50% Coursework. 50% ExamSummative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Exam | 50% |
| Coursework assignment(s) | 50% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Exam | 50% |
| Coursework assignment(s) | 50% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Exam | 50% |
| Coursework assignment(s) | 50% |
Repeat Information
Repeat type: Internal & External