Module Code - Title:
CS4136
-
TOPICS IN AI (SEMINAR SERIES)
Year Last Offered:
2025/6
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.
Research Findings Incorporated in to the Syllabus (If Relevant):
Prime Texts:
Stuart Russell, Peter Norvig (2020)
Artificial Intelligence: A Modern Approach (Pearson Series in Artifical Intelligence) 4th Edition
, Prentice Hall
Ian Goodfellow and Yoshua Bengio and Aaron Courville (2016)
Deep Learning
, MIT Press book
Charu Aggarwal (2018)
Neural Networks and Deep Learning
, Springer
Other Relevant Texts:
Programme(s) in which this Module is Offered:
Semester(s) Module is Offered:
Spring
Module Leader:
meghana.kshirsagar@ul.ie