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.
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.
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.
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 |
|---|---|
| Teaching | 30 |
| Independent Study | 120 |
| 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