CM50263: Artificial intelligence
[Page last updated: 09 August 2024]
Academic Year: | 2024/25 |
Owning Department/School: | Department of Computer Science |
Credits: | 6 [equivalent to 12 CATS credits] |
Notional Study Hours: | 120 |
Level: | Masters UG & PG (FHEQ level 7) |
Period: |
|
Assessment Summary: | CW 25%, EX 75% |
Assessment Detail: |
|
Supplementary Assessment: |
|
Requisites: | Before taking this module you must take CM50258 OR take CM50109 OR take another programming module |
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. 5. Critically evaluate state-of-the-art AI applications. |
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. |
Skills: | Use of IT (T/F,A) Problem solving (T/F,A),Communication (T/F,A), Critical thinking (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. |
Course availability: |
CM50263 is Optional on the following courses:Department of Computer Science
|
Notes:
|