Last modified: 18 Nov 2022 13:11
The course provides an introduction to Artificial Intelligence (AI). It discusses fundamental problems of AI and their computational solution via key concepts.
| Study Type | Undergraduate | Level | 3 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Offshore | Sustained Study | No |
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The course provides an introduction to Artificial Intelligence (AI). It discusses fundamental problems of AI and their computational solution via key concepts.
Content: Introduction and Agents; Uninformed search. Search; Informed search; Adversarial Search; Constraint Satisfaction Problems; Logical Agents, propositional reasoning; Probabilistic Reasoning under Uncertainty; Planning; Symbolic Machine Learning; Neural Nets.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
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| Knowledge Level | Thinking Skill | Outcome |
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| Assessment Type | Summative | Weighting | 50 | |
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| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Reflection | Create | Ability to apply AI concepts, techniques, and tools to creatively solve problems |
| Conceptual | Understand | Understanding of major issues, problems, solutions, and concepts in AI |
| Procedural | Evaluate | Ability to analyse and evaluate proposed AI solutions in their context |
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