Skip to main content

Trinity College Dublin, The University of Dublin

Menu Search

Module Descriptor School of Computer Science and Statistics

Module CodeCS7IS2
Module NameArtificial Intelligence
Module Short Title
Semester TaughtMT
Contact Hours

2 Lecture hours per week

Module PersonnelDr. Annalina Caputo
Learning Outcomes

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 in natural language processing, perception or robotics.
Learning Aims

This module aims to provide students with a thorough overview of the techniques that underlie intelligent systems and an ability to apply these techniques to real-world problems.

Module Content

Specific topics addressed in this module include:

  • Search;
  • Problem solving;
  • Knowledge and reasoning – representations, logic, reasoning;
  • Classical automated planning;
  • Representing and reasoning with uncertainty;
  • Learning;
  • Introductions to topics in Natural Language Processing, Perception, Robotics.
Recommended Reading List

Stuart Russell and Peter Norvig (2010) Artificial Intelligence: A Modern Approach, Third Edition. Upper Saddle River (NJ): Prentice Hall.

Module Prerequisites

CS7CS4 or CS4404 Machine Learning

Assessment Details

Coursework: 50%

Exam: 50%

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.

Module Website
Academic Year of Data2017/18