CM2203: Informatics
School | Cardiff School of Computer Science and Informatics |
Department Code | COMSC |
Module Code | CM2203 |
External Subject Code | 100370 |
Number of Credits | 10 |
Level | L5 |
Language of Delivery | English |
Module Leader | Dr Sylwia Polberg-Riener |
Semester | Spring Semester |
Academic Year | 2024/5 |
Outline Description of Module
The aim of this module is to provide the student with and understanding of the role data mining and data quality techniques play in our lives. The students will develop a basic toolbox allowing them to use methods for learning and evaluation information. This will be paired with a consideration of the ethical implications surrounding gathering and using information in an automated manner.
On completion of the module a student should be able to
- Execute and evaluate various techniques in knowledge discovery and data mining
- Analyse and critically evaluate methods for assuring quality of information
- Appraise the ethical implications and societal risks associated with data mining and data quality assurance
How the module will be delivered
Modules will be delivered through blended learning. You will be guided through learning activities appropriate to your module, which may include:
on-line resources that you work through at your own pace (e.g. videos, web resources, e-books, quizzes),
on-line interactive sessions to work with other students and staff (e.g. discussions, live streaming of presentations, live-coding, team meetings)
face to face small group sessions (e.g. help classes, feedback sessions)
Skills that will be practised and developed
Please refer to the learning outcomes.
How the module will be assessed
The module will be assessed with three portfolios consiting of a blend of tasks, which can include online exercises, coded tasks, short essays, independent inquiry, etc.
Assessment Breakdown
Type | % | Title | Duration(hrs) |
---|---|---|---|
Portfolio | 40 | Informatics Portfolio 1 | N/A |
Portfolio | 30 | Informatics Portfolio 2 | N/A |
Portfolio | 30 | Informatics Portfolio 3 | N/A |
Syllabus content
Similarity measures
Knowledge discovery process
Data mining
Classification
Clustering
Association rule learning
Data quality dimensions, activities and methodologies
Ethical considerations concerning gathering and using information