THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2021/2022

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Industrial Mathematics (MATH11231)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryIndustrial 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 None
Course Delivery Information
Academic year 2021/22, 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:
  1. Formulate mathematical and computational approaches for industrial problems.
  2. Develop and apply suitable numerical and analytical methods to such problems.
  3. Interpret and critically evaluate the underlying assumptions and results of these approaches.
  4. 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
KeywordsIndM,Industrial Mathematics
Contacts
Course organiserDr Benjamin Goddard
Tel: (0131 6)50 5127
Email: B.Goddard@ed.ac.uk
Course secretaryMiss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information