| Unit name | Principles of Computational Modelling |
|---|---|
| Unit code | SEMT20001 |
| Credit points | 20 |
| Level of study | I/5 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Homer |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
EMAT10100 Engineering Mathematics 1 (or equivalent) EMAT10704 Discrete Mathematics (or equivalent) SEMT1xxxx Computer Programming and Algorithms (or equivalent) |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Why is this unit important?
In this unit, you will learn how to translate mathematical descriptions of practical real-world problems into computational models, and demonstrate how those models are verified, validated, and calibrated. You’ll learn how to measure the performance of a computational model, and hence make an informed choice between the different possible approaches that might be available. You’ll also be able to tune the approach you select to produce solutions of a desired accuracy with the computational resources that you have available. You’ll also be able to explain and analyse why a computational modelling approach works (or doesn’t!) in terms of the underlying mathematical structures that underpin it. By the end of the unit, you’ll be able to implement the ideas for yourself, in code.
How does this unit fit into your programme of study
In year 1, you were introduced to computer programming, (perhaps for the first time). This unit aims to build on that knowledge, in the context of real-world problem-solving, and equip you with the mathematical and computational toolkit to design your own code to find a numerical solution of a mathematical problem, and to analyse the performance of a chosen method. You’ll use these skills extensively later in the programme, for example when implementing an agent-based reinforcement learning algorithm or writing code to solve a PDE, whether that’s in follow-on optional units or when building computational models in Mathematical and Data Modelling or Technical Project units.
An overview of content
Topics covered in the unit will include:
How will students, personally, be different as a result of the unit
By successfully completing this unit you will be able to think about a mathematical problem from a computational perspective. You’ll be able to write code that finds the solution to a mathematical system and make an informed choice from the different methods that are available. You’ll understand what’s going on inside the black box of different numerical methods, when they can and can’t be trusted, and how to tune them to meet your needs.
Learning Outcomes
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including video lectures, on-campus lecture/Q&A sessions, and formative self-directed exercises. The unit will be supported by weekly computer labs; these will provide student-centred on-campus learning through practical problem solving and, a supportive environment where students apply for themselves the theory and methods discussed in the unit. Students will be expected to actively participate in the lectures and labs, and engage with readings, self-directed exercises, and problem-solving activities.
Tasks which help you learn and prepare you for summative tasks (formative):
Weekly formative worksheets, with full worked solutions provided the following week. Feedback can be obtained through the weekly computer lab.
Tasks which count towards your unit mark (summative):
1 Summative Assessment, 100% - Coursework. This will assess all ILOs.
When assessment does not go to plan
Re-assessment takes the same form as the original summative assessment.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. SEMT20001).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
