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Module Themes

Thursday, 25 July, 2024

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
Enterprise, Innovation & Entrepreneurship (COMP30390) 1  5  Level 3 module
Social Simulation: Methods and Models (SOC40640) 1 10 *** FULL ***
Enviro-Tech Boot Camp (COMP30840) 2  5  Level 3 module
Ethical Hacking (COMP47860) 2  5   
Digital Media Ethics (IS30370) 2 5 Level 3 module; *** FULL ***
Digital Storytelling (IS30380) 2 5 Level 3 module; *** FULL ***
Digital Libraries (IS40560) 2 5  
Social Networks Online and Off (IS41510) 2 10  

Module title and code Semester Credits Comments
Data Mining (COMP40370) 1 5  
Connectionist Computing (COMP41390) 1 5  
Text Analytics (COMP41730) 1 5  
Machine Learning (blended delivery) (COMP47460) 1 5  
Machine Learning w/ Python (COMP47750) 1, 2 5  
Optimisation (COMP47790) 1 5  
Intro. to Quantum Computing (EEEN40680) 1 5 Must be taken as a pre-requisite for COMP47950 (see below)
Recommender Systems & Collective Intelligence (COMP31010) 2 5 Level 3 module; Module has programming prerequisites
Advanced Machine Learning (COMP47590) 2 5 Module has programming prerequisites
Deep Learning (COMP47650) 2 5 Prerequisites: statistics & calculus 
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
Information Theory (COMP30690) 1 5 Level 3 module
Formal Foundations 3 (COMP31020) 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
Software Engineering (COMP41670) 1 5 Prerequisite: object-oriented programming knowledge
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

Module title and code Semester Credits Comments
Information Security (COMP30940) 1 5 Level 3 module; note, this is a prerequisite for COMP41960 (see below)
Blockchain & Decentralisation (COMP41770) 1 5  
Technical Communication (online) (MEEN40820) 1 5 See MEEN40670 below. 
Bioinformatics (COMP40400) 2 5  
Advanced Information Security (COMP41960) 2 5 Prerequisite: COMP30940 (see above)
Introduction to Business of Biotech Skills (blended delivery) (BMOL30100) 2 5 Level 3 module
Technical Communication (MEEN40670) 2 5  
Decision Analytics (MIS30010) 2 5 Level 3 module

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 module(s) is September 7th. 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 2025 10
Agent-Oriented Software (COMP40040) Spring Jan 2026 10
Knowledge-based Techniques for Industrial Systems (COMP40080) Spring Jan 2026 10

Module Themes

Thursday, 25 July, 2024

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 1st. If you already have some knowledge of a language, but are uncertain of your level of proficiency, please contact or visit the Help Desk for a language consultation.   

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)