ACM30130

Learning Outcomes:

On successful completion of this module, students should be able to:
• Work with both symbolic and numerical computational tools for rapid modelling, analysis, simulation and visualisation.
• Work in a scientific computing environment, including the use of Linux, ssh and a command line interface.
• Integrate computational and mathematical skills for problem solving.
• Develop realistic modelling frameworks.
• Produce informative graphics and visualisation that enhance understanding of a problem.
• To identify and apply current research analysis to applied problems.
• Write, present and communicate mathematics in an applied and computational setting.

Indicative Module Content:

Topics will be drawn from a broad base. Representative topics include:
• Programming in Python and Mathematica
• Scientific computing tools including Linux, ssh and a command line interface
• Shooting methods for boundary value problems
• Finite difference methods
• Symbolic computer algebra
• Matched asymptotic expansions

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


 

Student Effort Hours:

Approaches to Teaching and Learning:

Hybrid lectures with a mix of theory, live coding examples, and lab-based programming exercises. In-class teaching will be accompanied by self study and problem-based learning outside of class.

Generative AI tools will not be permitted in the coding exams, but their use can be explored outside of these both as a learning tool and as a coding assistant, including for the take-home assignments. Short reflections on students' use of AI will be mandatory for each assignment.

Requirements, Exclusions and Recommendations

Learning Requirements:

Students must have taken ACM20030 Computational Science or an equivalent.

Module Requisites and Incompatibles

Pre-requisite:
ACM20030 - Computational Science


 

Assessment Strategy

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.

 

Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.