Last modified: 23 Jul 2024 11:06
This course provides an introduction to machine learning and data mining. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time-series analysis, neural networks, and many other techniques. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.
Study Type | Undergraduate | Level | 3 |
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Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
Campus | Offshore | Sustained Study | No |
Co-ordinators |
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This course introduces the student to machine learning techniques, as the means for computer systems to extract useful information out of data. Topics include:
Information on contact teaching time is available from the course guide.
Assessment Type | Summative | Weighting | 70 | |
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Assessment Weeks | Feedback Weeks | |||
Feedback |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for analysis. |
Procedural | Apply | Ability to appropriately present the results of data analysis. |
Procedural | Evaluate | Knowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done. |
Procedural | Evaluate | Ability to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context. |
Assessment Type | Summative | Weighting | 30 | |
---|---|---|---|---|
Assessment Weeks | Feedback Weeks | |||
Feedback |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for analysis. |
Procedural | Apply | Ability to appropriately present the results of data analysis. |
Procedural | Evaluate | Knowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done. |
Procedural | Evaluate | Ability to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context. |
There are no assessments for this course.
Assessment Type | Summative | Weighting | 100 | |
---|---|---|---|---|
Assessment Weeks | Feedback Weeks | |||
Feedback |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
|
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
Procedural | Apply | Ability to appropriately present the results of data analysis. |
Procedural | Evaluate | Knowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done. |
Procedural | Evaluate | Ability to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context. |
Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for analysis. |
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