Last modified: 09 Nov 2022 11:20
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 | 4 |
|---|---|---|---|
| Session | First Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
|
||
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.
Content:
Obtaining, preparing, managing, and presenting data
Supervised learning, classification, regression
Unsupervised learning, clustering
Decision-tree learning
Neural networks and deep learning
Case-studies and applications
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Written Feedback |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for 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 | 15 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Written Feedback |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for 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 | 70 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to identify, prepare, and manage appropriate datasets for analysis. |
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 | Create | 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. |
We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.
