Last modified: 23 Jul 2024 11:05
This is a look at data science with respect to business intelligence, dashboards whereby students learn to create applications for handling larger datasets, as well as as a knowledge of visualisations for different situations. This also covers networking and fault tolerance issues as part of learning to development for continuous integration and continuous deployment of the applications.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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We will explore a range of different datasets that characterise a range of different common challenges to learn different ways in which we might visualise them. We will also learn how to host these applications in the cloud. The topics covered include:
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 40 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
MCQ Quiz |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | The ability to refactor and test applications to ensure the appropriate standard of quality. |
| Procedural | Apply | An ability to use agile requirements gathering to develop an application meeting client needs. |
| Procedural | Create | An ability to apply appropriate continuous integration and continuous deployment techniques to application development. |
| Procedural | Evaluate | An ability to apply lightweight data science approaches to develop a dashboard application. |
| Procedural | Evaluate | An ability to design dimensional data models to support a software application. |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
(Group Exercise) |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | An ability to use agile requirements gathering to develop an application meeting client needs. |
| Procedural | Evaluate | An ability to apply lightweight data science approaches to develop a dashboard application. |
| Procedural | Evaluate | An ability to design dimensional data models to support a software application. |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
(Individual Exercise) |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | The ability to refactor and test applications to ensure the appropriate standard of quality. |
| Procedural | Apply | An ability to use agile requirements gathering to develop an application meeting client needs. |
| Procedural | Create | An ability to apply appropriate continuous integration and continuous deployment techniques to application development. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Individual tasks will be assigned in place of group work |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | An ability to use agile requirements gathering to develop an application meeting client needs. |
| Conceptual | Understand | The ability to refactor and test applications to ensure the appropriate standard of quality. |
| Procedural | Evaluate | An ability to design dimensional data models to support a software application. |
| Procedural | Create | An ability to apply appropriate continuous integration and continuous deployment techniques to application development. |
| Procedural | Evaluate | An ability to apply lightweight data science approaches to develop a dashboard application. |
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