Module Code - Title:
CS4136
-
TOPICS IN AI (SEMINAR SERIES)
Year Last Offered:
2026/7
Hours Per Week:
Grading Type:
N
Prerequisite Modules:
Rationale and Purpose of the Module:
The rationale and purpose of this module is to introduce students to a variety of disparate topics in Artificial Intelligence. Topics vary from one offering to the next and are likely to be drawn from the following list: natural language processing, machine vision, games, search, genetic algorithms, robotics, AI and society, concurrent programming, knowledge representation, decision-making under uncertainty, reinforcement learning, agents, foundations.
Syllabus:
This will take the form of an intensive series of workshops, seminars and lectures by industry and academic experts, both nationally and internationally.
Learning Outcomes:
Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)
On successful completion of this module students will be able to:
Demonstrate knowledge and understanding of core and open challenges in AI.
Select and synthesize research papers on a method or research challenge.
Evaluate AI concepts and prototypes from both a qualitative and quantitative perspective
Affective (Attitudes and Values)
On successful completion of this module, students will be able to:
Determine and execute affective requirements gathering methods to develop an appropriate AI solution
Psychomotor (Physical Skills)
n/a
How the Module will be Taught and what will be the Learning Experiences of the Students:
Currently AI is constantly evolving and expanding, and is playing a greater role in modern society. This technology triggers great shifts in such industries as healthcare, automotive, retail, construction, banking, advertising. This module will be taught as a series of seminar on seminal and contemporary AI issues. The module will be taught as a series of talks that will give the students an opportunity to hear from national and international experts in different areas AI and its application to various domains.
Prime Texts:
Stuart Russell, Peter Norvig (2020)
Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence) 4th Edition
, Prentice Hall
Charu Aggarwal (2018)
Neural Networks and Deep Learning
, Springer
Ian Goodfellow and Yoshua Bengio and Aaron Courville (2016)
Deep Learning
, MIT Press book
Other Relevant Texts:
Programme(s) in which this Module is Offered:
BACHELOR OF SCIENCE IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Semester(s) Module is Offered:
Spring
Module Leader:
meghana.kshirsagar@ul.ie