Cognitive Science Modules

This is the proposed timetable for 2016/2017. All details are tentative and subject to change. The final timetable will be published in September 2016.

Students typically take eight of the ten modules listed below. All module choices must be discussed with the course director. Substitutions on an individual basis may be possible.

First semester, Autumn 2016
Mon Tue Wed Thurs Fri
9:00-11:00

PSY 40020 Funadamentals of Cognitive Neuropsychology

Ciara Greene
Arts E114
  11:00-13:00

COMP 40250
Introduction to Cognitive Psychology

Fintan Costello
CSI B1.08
   
11:00 - 13:00

COMP 47230
Introduction to Cognitive Science

Fred Cummins
CSI B1.09
  14:00-16:00

PHIL 40010
Consciousness, Agency and the Self

Markus Scholsser
D522, School of Philosophy, Newman Building.
11:00-13:00

PHIL 41440
Critiquing Scientific Inference

Mikio Akagi
D522, School of Philosophy, Newman Building.
 
Second semester, Spring 2017
10:00-11:00

PSY 40550
Readings in Visual and Social Cognition

Nuala Brady
Arts. Th O.
  10:00-11:00

PSY 40550
Readings in Visual and Social Cognition

Nuala Brady
Arts, Th O.
   
11:00-13:00

COMP 40260
Connectionism and Dynamical Systems

Fred Cummins
CSI B1.08
  11:00-13:00

COMP 40270
Cognitive Modelling

Fintan Costello
CSI B1.08
   
14:00-16:00

COMP 40260
Connectionism and Dynamical Systems

Lab
Fred Cummins
CSI B1.08
  14:00-16:00

COMP 40280
Topics in Cognitive Science: Post-Cognitivist Seminar

Fred Cummins
CSI Coffee Area Meeting Room

COMP 40630
Human Computer Interaction

David Coyle
H2.20 (Science Hub)
 

Non-core modules of possible relevance

Depending on the background of individual students, some substitutions to the standard suite of modules may be appropriate. Some modules of possible relevance are listed here, but this list does not try to be exhaustive.

STAT 40430 Biostatistics (7.5 credits)
Statistics module for those without any statistical background.
Semester 1. Timetable t.b.a.
Lecturer: Nial Friel
COMP 47490 Machine Learning (5 credits)
The objective of this module is to familiarise students with the fundamental theoretical concepts in machine learning, as well as to instruct students in the practical aspects of applying machine learning algorithms. Key techniques in supervised machine learning will be covered, such as classification using decision trees and nearest neighbour algorithms, and regression analysis. A particular emphasis will be placed on the evaluation of the performance of these algorithms. In unsupervised machine learning, a number of popular clustering algorithms will be presented in detail. Further topics and applications of machine learning will also be introduced. COMP47490 requires strong mathematical ability, as some of the algorithms require some understanding of linear algebra and statistical concepts.
A follow on module, COMP 47590 Advanced Machine LEarning in Semester 2 is also available (5 credits).
Semester 1. Timetabling details t.b.a.
Lecturer: Derek Greene
IS 40610 UXD: User-Centered Design (5 credits)
Technology is now ubiquitously used in our everyday life. We have countless interactions with interfaces and information systems across our day be it with social media, mobile apps, as well as more traditional desktop oriented interactions. This course will explore the discipline of human-computer interaction (HCI), a discipline which focuses on the design of user-centred technology interactions and the effect that design and technology interaction has on people's behaviours, perceptions and emotions. The course will teach students 1) how to design and evaluate technology interactions to ensure truly user centred design as well as 2) more theoretical insights on how interface design affects user behaviours, emotions and performance. Students will be asked to create their own design solution for a specific information system use case as well as deeply explore cutting edge research in an area of academic research in HCI. Students will be asked to think creatively, work together on a practical design led project as well as study in depth what it means to place the human at the centre of technology design.
Semester 1. Timetabling t.b.a.
Lecturer: Ben Cowan