- Offered for Year: 2023/24
- Module Leader(s): Dr Chris Graham
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
|
Semester 1 Credit Value:
|
10
|
|
ECTS Credits:
|
5.0
|
Aims
To reinforce the computing in Python studied at Stage 1, and to move towards expectations of more independent programming. To introduce a wider range of mathematical techniques within Python, including methods that will be useful towards future project work.
Module Summary
Computing methods are of great use in a wide range of applications applied mathematics. This module builds on the methods introduced at Stage 1, introducing additional techniques, some of increasing mathematical and computational sophistication. In implementing these methods, students will attain increasing competence with mathematical computing, and an increasing ability to use such methods independently, towards project-orientated goals.
Outline Of Syllabus
? Plotting of vector fields and trajectories.
? Curve fitting (e.g. least squares fitting of known function to data).
? Root finding (Newton-Raphson and Python solvers).
? Numerical derivatives through finite difference, and related techniques of numerical integration.
? Numerical solution of ordinary differential equations and applications to dynamical systems.
Teaching Methods
Teaching Activities
| Category |
Activity |
Number |
Length |
Student Hours |
Comment |
|---|
| Guided Independent Study | Assessment preparation and completion | 21 | 1:00 | 21:00 | Completion of in course assessment |
| Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | Lectures |
| Scheduled Learning And Teaching Activities | Lecture | 22 | 1:00 | 22:00 | Computer Practicals |
| Guided Independent Study | Independent study | 46 | 1:00 | 46:00 | Preparation time for lectures, background reading, coursework review |
| Total | | | | 100:00 | |
Jointly Taught With
| Code |
Title |
|---|
| MAS2806 | Scientific Computation with Python |
Teaching Rationale And Relationship
Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Practicals are used to help develop the students’ abilities at applying the theory to solving problems.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description |
Length |
Semester |
When Set |
Percentage |
Comment |
|---|
| Digital Examination | 120 | 1 | A | 70 | Digital Examination |
Exam Pairings
| Module Code |
Module Title |
Semester |
Comment |
|---|
| MAS2806 | Scientific Computation with Python | 1 | N/A |
Other Assessment
| Description |
Semester |
When Set |
Percentage |
Comment |
|---|
| Prob solv exercises | 1 | M | 15 | Problem-solving exercises assessment |
| Prob solv exercises | 1 | M | 15 | Problem-solving exercises assessment |
Assessment Rationale And Relationship
A substantial class test is appropriate for the assessment of the material in this module. The coursework assignment allows the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; this assessment has a secondary formative purpose as well as a primary summative purpose.
Reading Lists
Timetable
