ACM30130 Advanced Computational Science

Academic Year 2023/2024

Mathematical and computational techniques will be developed to provide integrative methodologies for solving applied problems. Theoretical concepts will be covered in lectures and will be supported by lab-based programming exercises, assignments and projects.

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Curricular information is subject to change

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
• Applied queuing theory

Student Effort Hours: 
Student Effort Type Hours


Computer Aided Lab


Specified Learning Activities


Autonomous Student Learning




Approaches to Teaching and Learning:
Lectures, lab-based programming exercises, enquiry and problem-based learning. 
Requirements, Exclusions and Recommendations
Learning Requirements:

Students must have taken ACM20030 Computational Science or an equivalent.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Class Test: Two computer-based coding exams Throughout the Trimester n/a Standard conversion grade scale 40% No


Assignment: Take home assignments Throughout the Trimester n/a Standard conversion grade scale 40% No



Carry forward of passed components
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment
• Online automated feedback

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Mr Jake Williams Lecturer / Co-Lecturer