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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Foundations of Artificial Intelligence
Module Code CA686I
School School of Computing
Module Co-ordinatorSemester 1: Mark Humphrys
Semester 2: Mark Humphrys
Autumn: Mark Humphrys
Module TeachersMark Humphrys
NFQ level 9 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Repeat examination
Repeat both the CA and the exam.

This module will provide students with a theoretical and practical grounding in the most important foundational topics in Artificial Intelligence, e.g. AI as search, problem solving, machine learning, machine evolution, perceiving and acting.

Learning Outcomes

1. Gain a detailed understanding of the general topic of artificial intelligence, including its philosophical foundations, and present status and future developments.
2. Understand, code and evaluate search techniques in AI, including constraint satisfaction, heuristic search and adversarial search.
3. Understand, code and evaluate computational evolution techniques in AI, including genetic algorithms to solve large-dimensional problems.
4. Understand, code and evaluate machine learning techniques in AI, including some or all of supervised learning, neural networks, knowledge in learning, probabilistic learning, and reinforcement learning.

Workload Full-time hours per semester
Type Hours Description
Lecture36No Description
Assignment Completion24No Description
Independent Study120No Description
Total Workload: 180

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Assessment Breakdown
Continuous Assessment40% Examination Weight60%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Digital ProjectAI coding project.40%n/a
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • Stuart Russell, Peter Norvig: 2016, Artificial Intelligence: A Modern Approach,,
Other Resources

Programme or List of Programmes
MCMM.Sc. in Computing

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