Module Descriptor School of Computer Science and Statistics
|Module Name||Artificial Intelligence|
|Module Short Title|
2 Lecture hours per week
|Module Personnel||Dr. Ivana Dusparic|
On successful completion of this module a student should be able to:
IS2LO1 Appreciate the scope, applications and limitations of artificial intelligence;
IS2LO2 Choose and use appropriate representations for various kinds of knowledge;
IS2LO3 Comprehend and apply search, reasoning and planning strategies;
IS2LO4 Develop intelligent systems that handle uncertainty;
IS2LO5 Apply knowledge representation, reasoning, and machine learning techniques to real-world problems
This module aims to provide students with a thorough overview of the AI techniques that underlie intelligent systems and an ability to apply these techniques to real-world problems.
Specific topics addressed in this module include:
|Recommended Reading List|
Stuart Russell and Peter Norvig (2010) Artificial Intelligence: A Modern Approach, Third Edition. Upper Saddle River (NJ): Prentice Hall.
CS7CS4 or CS4404 Machine Learning
Assessment is by written exam (50%) and coursework (50%).
Assessment in the Supplemental session will be based on 100% exam.
Assignments will provide practical experience, in both theory and programming.
|Academic Year of Data||2018/19|