Postgraduate Course: Industrial Mathematics (MATH11231)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Industrial Mathematics focuses on problems which come from industry,
aiming for relevant and applicable solutions. This typically requires
analytical and problem-solving skills, built upon a foundation of pure and
applied mathematics, statistics, and computing. Such mathematical
modelling, simulation, and optimisation are key tools in the development
of efficient, robust, and productive industrial processes and strategies.
These approaches enable evidence-informed decisions in a wide range
of industries, from manufacturing to policy-making. It is crucial that such
work is undertaken by well-trained experts, who can also communicate
the results clearly to a broad audience.
This course will introduce the key steps that take an industrial problem
through to an advisory report, using a wide range of tools including
model formulation, data analysis, computation, and analytical solution.
The course will give students the opportunity to tackle real-world,
industrial problems of current interest, through which they will learn both
relevant mathematical approaches, and the skills necessary to produce
industrial-style reports. |
| Course description |
The course employs a hands-on approach to tackling real-world,
industrial applications through a wide range of mathematical and
computational approaches. This will allow students to understand the
importance to industry of the mathematics they have learnt in previous
courses. They will gain further mathematical and computational
knowledge alongside receiving expert guidance through the process of
finding solutions to problems of current interest, as well as the skills
necessary to present their findings in an industrial setting.
The topics studied will vary year-on-year.
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Honours Differential Equations (MATH10066) AND
Numerical Linear Algebra (MATH10098) AND
Probability (MATH08066)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Note that PGT students on School of Mathematics MSc programmes are not required to have taken pre-requisite courses, but they are advised to check that they have studied the material covered in the syllabus of each pre-requisite course before enrolling. |
Course Delivery Information
|
| Academic year 2024/25, Not available to visiting students (SS1)
|
Quota: 50 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
68 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework : 100%
Examination : 0% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Formulate mathematical and computational approaches for industrial problems.
- Develop and apply suitable numerical and analytical methods to such problems.
- Interpret and critically evaluate the underlying assumptions and results of these approaches.
- Communicate key mathematical findings in a manner appropriate for a broad audience.
|
Reading List
| This will vary depending on the topics chosen |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | IndM,Industrial Mathematics |
Contacts
| Course organiser | Dr Benjamin Goddard
Tel: (0131 6)50 5127
Email: B.Goddard@ed.ac.uk |
Course secretary | Miss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk |
|
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