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 Academic Year: | 2018/9 | |
| Owning Department/School: | Department of Computer Science | |
| Credits: | 6 [equivalent to 12 CATS credits] | |
| Notional Study Hours: | 120 | |
| Level: | Intermediate (FHEQ level 5) | |
| Period: |
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| Assessment Summary: | CW 25%, EX 75% | |
| Assessment Detail: |
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| Supplementary Assessment: |
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| Requisites: | Before taking this module you must ( take CM10228 OR take XX10190 ) AND take CM20254 | |
| Description:
| Aims: To present a detailed introduction to formal artificial intelligence To establish a practical understanding of intelligence and computation as strategies for problem solving, and the nature of the problems amenable to various established strategies and approaches. Learning Outcomes: On completion of this unit, students will be able to: 1. Understand a wide range of AI techniques, their advantages and disadvantages. 2. Appreciate AI as a mechanism to deal with computationally hard problems in a practical manner 3. Understand the concepts of formal AI and put them into practice. 4. Write small to medium sized programs for aspects of Artificial Intelligence. Skills: Use of IT (T/F,A) Problem solving (T/F,A). Content: Goals and foundations of AI Problem solving (uninformed, heuristic, and adversarial search; constraint satisfaction) Logical reasoning (propositional logic, first-order logic, logic programming) Probabilistic reasoning (probability models, Bayesian networks) Machine learning (possible topics include decision trees, nearest-neighbor methods, reinforcement learning, neural networks, support vector machines, boosting). State-of-the-art AI applications will be discussed throughout the unit. | Before taking this module you must ( take CM10228 OR take XX10190 ) AND take CM20254 |
| Programme availability: |
CM20252 is Compulsory on the following programmes:Department of Computer Science
CM20252 is Optional on the following programmes:Department of Computer Science
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Notes:
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