Module 23069 (2010)
Syllabus page 2010/2011
06-23069
Introduction to AI
Level 1/C
Nicholas Hawes:5
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
See the
Module Web Page [2010]
for module material and further useful links.
Outline
This module provides a general introduction to artificial intelligence, its techniques, and main subfields. The principal focus of the module will be on the common underlying ideas, such as knowledge representation, rule based systems, search, and learning. It will provide a foundation for further study of specific areas of artificial intelligence.
Aims
The aims of this module are to:
- provide a general introduction to artificial intelligence, its techniques and its main subfields
- give an overview of key underlying ideas, such as knowledge representation, reasoning, search, and learning
- demonstrate the need for different approaches for different problems
- provide a foundation for further study of specific areas of artificial intelligence
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | discuss the major issues and techniques in a variety of sub-fields of AI, such as vision, robotics, natural language processing, planning, probabilistic reasoning, and machine learning | Examination |
| 2 | compare common AI techniques, describing their strengths and limitations | Examination |
| 3 | apply a variety of standard AI techniques to simple examples | Examination, Coursework |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
3 hrs/week of lectures, guest seminars, and exercise sessions
Contact Hours:
Assessment
- Sessional: Coursework (20%), 1.5 hr examination (80%).
- Supplementary (where allowed): 1.5 hr examination only (100%)
Recommended Books
| Title | Author(s) | Publisher, Date |
| Artificial Intelligence: A Modern Approach (2nd edn) | S Russell & P Norvig | Prentice Hall, 2003 |
Detailed Syllabus
- Introduction and background
- Decision Tree learning
- Neural Networks
- Probabilistic AI and Bayes inference
- Uninformed and informed search
- Planning
- Evolutionary Computation
Last updated: 23 September 2010
Source file: /internal/modules/COMSCI/2010/xml/23069.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus