Last modified: 05 Dec 2025 16:16
This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Offshore | Sustained Study | No |
| Co-ordinators |
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This course presents a cross-section of fundamental AI techniques and technologies. Lectures will cover core concepts, theories, mechanisms and results, while practicals and tutorials will allow students to implement and use these techniques. Example topics covered in this course include approaches to searching in AI; automated planning and scheduling; AI techniques used in robotics; knowledge representation and natural language understanding.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Duration: 2 hours |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Create | Students will develop the ability to think analytically and creatively about classic AI theories and techniques. |
| Conceptual | Understand | Students will demonstrate mastery of classic artificial intelligence theories and techniques. |
| Procedural | Analyse | Students will demonstrate the ability to apply relevant analysis techniques, and to contrast and compare AI techniques and their applicability to specific or classes of problems. |
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Word count: 2,500 |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Create | Students will develop the ability to think analytically and creatively about classic AI theories and techniques. |
| Conceptual | Understand | Students will demonstrate mastery of classic artificial intelligence theories and techniques. |
| Procedural | Analyse | Students will demonstrate the ability to apply relevant analysis techniques, and to contrast and compare AI techniques and their applicability to specific or classes of problems. |
| Reflection | Evaluate | Students will demonstrate an ability to perform an in-depth analysis of classical AI techniques and theories, and to evaluate and communicate their findings at suitable technical depth level. |
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Word count: 800 |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Create | Students will develop the ability to think analytically and creatively about classic AI theories and techniques. |
| Conceptual | Understand | Students will demonstrate mastery of classic artificial intelligence theories and techniques. |
| Procedural | Analyse | Students will demonstrate the ability to apply relevant analysis techniques, and to contrast and compare AI techniques and their applicability to specific or classes of problems. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Students will demonstrate mastery of classic artificial intelligence theories and techniques. |
| Conceptual | Create | Students will develop the ability to think analytically and creatively about classic AI theories and techniques. |
| Procedural | Analyse | Students will demonstrate the ability to apply relevant analysis techniques, and to contrast and compare AI techniques and their applicability to specific or classes of problems. |
| Reflection | Evaluate | Students will demonstrate an ability to perform an in-depth analysis of classical AI techniques and theories, and to evaluate and communicate their findings at suitable technical depth level. |
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