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Module Themes

Thursday, 27 July, 2023

Modules are listed below grouped into themes to make it easier to identify related modules. There is no requirement to select within one, two, or any number of themes.

For any module you are interested in taking, please read the module descriptor carefully and check the official timetable to make sure you have no clashes in your own selections.  If the module title is followed by the note (Approval reqd), you must obtain permission from the module coordinator directly before enrolling.

Students within the Negotiated Learning programme may take no more than 20 credits at Level 3 or below, and no more than 15 credits that are not COMP coded.

Module title and code Semester Credits Comments
Data Mining (COMP40370) 1 5  
Connectionist Computing (COMP41390) 1 5 *** FULL ***
Text Analytics (COMP41730) 1 5  
Machine Learning (COMP47460) 1 5  
Machine Learning w/ Python (COMP47750) 1 5  
Intro. to Quantum Computing (EEEN40680) 1 5  
Recommender Systems & Collective Intelligence (COMP47580) 2 5 Module has programming prerequisites
Advanced Machine Learning (COMP47590) 2 5 Module has programming prerequisites
Deep Learning (COMP47650) 2 5 Prerequisites: statistics & calculus *** FULL ***
Optimisation (COMP47790) 2 5 *** FULL ***
Quantum Machine Learning (COMP47950) 2 5 Prerequisite: EEEN40680 (Intro. to Quantum Computing)
Machine Learning w/ Python (online) (COMP47990) 2 5  
Statistical Machine Learning (STAT30270) 2 5 Level 3 module; Approval required
Statistical Machine Learning (online) (STAT40750) 2 5 Approval required

Module title and code Semester Credits Comments
Data Programming with R (STAT30340) 1 5 Level 3 module; Approval required
Introduction to Data Analytics (online) (STAT40720) 1 5 Approval required
Data Programming with R (online) (STAT40730) 1 5 Approval required
Data Programming with Python (online) (STAT40800) 1 5 Approval required
Data Science in Python (COMP41680) 2 5  
Big Data Programming (COMP47470) 1, 2 5 Autumn (Sem 1) is *** FULL *** 
Data Science in Python (blended) (COMP47670) 1, 2 5 Autumn (Sem 1) is *** FULL ***

Module title and code Semester Credits Comments
Foundations of Computing (COMP30010) 1 5 Level 3 module
Information Theory (COMP30690) 1 5 Level 3 module
Partial Differential Equations (ACM30220) 1 5 Level 3 module
Numerical Algorithms (ACM40290) 1 5  
Monte Carlo Inference (STAT40400) 1 5 Approval required
Time Series Analysis (STAT40700) 1 5 Approval required
Multivariate Analysis (STAT40150) 2 5 Approval required
Multivariate Analysis (online) (STAT40740) 2 5 Approval required

Module title and code Semester Credits Comments
Java Programming (COMP20300) 1 5 Level 2 module
Multi-paradigm Programming (COMP30950) 1 5 Level 3 module; *** FULL ***
Software Engineering (COMP41670) 1 5 Prerequisite: object-oriented programming knowledge; *** FULL ***
Swift programming for App Dev using UIKit and SwiftUI (COMP47390) 1 5 Prerequisite: good programming skills
Exploring Ruby (COMP47530) 1 5  
Game Development (COMP30540) 2 5 Level 3 module
Contemporary Software Development (COMP47480) 2 5 Prerequisites: object-oriented programming; familiarity with Java; e.g. material covered in COMP30070 or COMP30950 as adequate
Advanced Data Structures in Java (online) (COMP47500) 2 10

In exceptional circumstances, NL students are able to select a number of modules from the Masters in Advanced Software Engineering (ASE) programme. Students must have a minimum of 2 years experience in a professional software engineering environment after their university degree to be eligible for these modules, and must be approved by the ASE Director. Please note that the deadline to apply for the Autumn trimester modules is September 10th. See this important set of slides for further information on the modules, their pre-requisites, etc.

Module title and code Trimester Start date Credits
High Performance Computing (COMP40730) Autumn Sept 2023 10 
Agent-oriented Software (COMP40040) Spring Jan 2024 10 
Knowledge-based Techniques for Industrial Systems (COMP40080) Spring Jan 2024 10 

Module Themes

Thursday, 27 July, 2023

Elective Module Options

In addition to the modules listed above, it may be appropriate, in individual cases, to substitute electives drawn from across the university. Inclusion of any elective modules must be signed off by your advisor during your student needs assessment.

Popular elective options include foreign language modules, taught from the Centre for English and Global Languages. Foreign language electives are described here. If you are interested in taking a language module, please complete (opens in a new window)this form no earlier than the week of September 4th. 

Students with specialization in Artificial Intelligence and Cognitive Science may be interested in modules from the Cognitive Science programme, which are listed (opens in a new window)here, and timetable details are provided (opens in a new window)here.

Students on the MSc Negotiated Learning programme must take a minimum of 45 taught credits from the School of Computer Science (COMP coded modules), and no more than 20 credits at level 3 or below.

UCD School of Computer Science

University College Dublin, Belfield, Dublin 4, Ireland, D04 V1W8.
T: +353 1 716 2483 | E: computerscience@ucd.ie | Location Map(opens in a new window)