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MAS2806 : Scientific Computation with Python

  • Offered for Year: 2022/23
  • Module Leader(s): Dr Chris Graham
  • Owning School: Mathematics, Statistics and Physics
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 10
ECTS Credits: 5.0


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 ActivitiesLecture111:0011:00Problem Classes – Synchronous On-Line
Guided Independent StudyAssessment preparation and completion151:0015:00Completion of in course assessment
Guided Independent StudyAssessment preparation and completion117:0017:00Revision and exam completion
Scheduled Learning And Teaching ActivitiesLecture221:0022:00Computer Practicals – Present in Person
Guided Independent StudyIndependent study351:0035:00Preparation time for lectures, background reading, coursework review
Jointly Taught With
Code Title
PHY2039Scientific 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

Description Length Semester When Set Percentage Comment
PC Examination1201A70PC Examination
Exam Pairings
Module Code Module Title Semester Comment
PHY2039Scientific Computation with Python1N/A
Other Assessment
Description Semester When Set Percentage Comment
Prob solv exercises1M30Problem-solving exercises
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