Incoming Study Abroad and Exchange students must contact and seek approval from school prior to enrolling
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
Scheduled Learning And Teaching Activities
Lecture
22
1:00
22:00
Computer Practicals – Present in Person
Scheduled Learning And Teaching Activities
Lecture
11
1:00
11:00
Problem Classes – Synchronous On-Line
Guided Independent Study
Assessment preparation and completion
15
1:00
15:00
Completion of in course assessment
Guided Independent Study
Independent study
52
1:00
52:00
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
PC Examination
120
1
A
50
Off-campus test
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
25
Problem-solving exercises
Prob solv exercises
1
M
25
Problem-solving exercises
Assessment Rationale And Relationship
A substantial class test is appropriate for the assessment of the material in this module. The coursework assignments allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; these assessments have a secondary formative purpose as well as their primary summative purpose.
