Last modified: 21 Aug 2025 13:46
This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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The Applied AI course will give a firm grasp of AI, its applications, its challenges related to commercial, social, and regulatory aspects with real-world use cases. On completion of this course, students will be able to apply the theoretical and practical knowledge they have gained on previous modules to undertake several AI mini-projects. Each project will exercise AI application libraries (e.g., TensorFlow or Keras), and students will therefore understand how AI techniques e.g., classifier and neural network systems, reinforcement learning systems and simulation/evaluation systems, can be combined to create an end-to-end deployable AI solution. They will also be aware of the additional challenges an AI developer has to keep in mind, especially regarding the performance, decision accuracy, ethical, regulatory and social aspects.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Group Report 2 (1,500 words, worth 30% of the overall grade). Peer assessment will form part of students' individual marks. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Students will be able to document – in a reproducible manner – their approach to AI system construction. |
| Conceptual | Apply | Students will be able to combine different components into an end-to-end solution. |
| Conceptual | Evaluate | Students will be able to validate the effectiveness of their solution. |
| Conceptual | Understand | Students will understand how libraries for AI system creation are applied and used in practice. |
| Reflection | Analyse | Students will reflect on their new knowledge and apply it to a practical example. |
| Reflection | Evaluate | Students will be able to reflect and modify their design in response to validation of an AI system’s performance. |
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Individual Report 2 (1,200 words, worth 20% of the overall grade). |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Students will be able to document – in a reproducible manner – their approach to AI system construction. |
| Conceptual | Apply | Students will be able to combine different components into an end-to-end solution. |
| Conceptual | Evaluate | Students will be able to validate the effectiveness of their solution. |
| Conceptual | Understand | Students will understand how libraries for AI system creation are applied and used in practice. |
| Reflection | Analyse | Students will reflect on their new knowledge and apply it to a practical example. |
| Reflection | Evaluate | Students will be able to reflect and modify their design in response to validation of an AI system’s performance. |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Group Report 1 (1,500 words, worth 30% of the overall grade). Peer assessment will form part of students' individual marks. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Students will be able to document – in a reproducible manner – their approach to AI system construction. |
| Conceptual | Apply | Students will be able to combine different components into an end-to-end solution. |
| Conceptual | Evaluate | Students will be able to validate the effectiveness of their solution. |
| Conceptual | Understand | Students will understand how libraries for AI system creation are applied and used in practice. |
| Reflection | Analyse | Students will reflect on their new knowledge and apply it to a practical example. |
| Reflection | Evaluate | Students will be able to reflect and modify their design in response to validation of an AI system’s performance. |
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Individual Report 1 (1,200 words, worth 20% of the overall grade). |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Students will be able to document – in a reproducible manner – their approach to AI system construction. |
| Conceptual | Apply | Students will be able to combine different components into an end-to-end solution. |
| Conceptual | Evaluate | Students will be able to validate the effectiveness of their solution. |
| Conceptual | Understand | Students will understand how libraries for AI system creation are applied and used in practice. |
| Reflection | Analyse | Students will reflect on their new knowledge and apply it to a practical example. |
| Reflection | Evaluate | Students will be able to reflect and modify their design in response to validation of an AI system’s performance. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
In the case of resits, individual tasks will be provided instead of groupwork. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Apply | Students will be able to document – in a reproducible manner – their approach to AI system construction. |
| Conceptual | Apply | Students will be able to combine different components into an end-to-end solution. |
| Conceptual | Understand | Students will understand how libraries for AI system creation are applied and used in practice. |
| Reflection | Evaluate | Students will be able to reflect and modify their design in response to validation of an AI system’s performance. |
| Reflection | Analyse | Students will reflect on their new knowledge and apply it to a practical example. |
| Conceptual | Evaluate | Students will be able to validate the effectiveness of their solution. |
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