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ACM30130

Academic Year 2024/2025

Advanced Computational Science (ACM30130)

Subject:
Applied & Computational Maths
College:
Science
School:
Mathematics & Statistics
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Dr Chris Howland
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

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.

About this Module

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

Student Effort Hours:
Student Effort Type Hours
Lectures

12
Computer Aided Lab

24
Specified Learning Activities

36
Autonomous Student Learning

36
Total

108

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 Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): Take home assignments Week 2, Week 4, Week 8, Week 10 Standard conversion grade scale 40% No
60
 No
Exam (In-person): Computer-based coding exams Week 6, Week 12 Standard conversion grade scale 40% No
40
 No

Carry forward of passed components
Yes
 

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

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.
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Mon 15:00 - 15:50
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Thurs 10:00 - 10:50
Autumn Lecture Offering 1 Week(s) - Autumn: All Weeks Tues 15:00 - 15:50
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