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Module

MAS1803 : Problem Solving with Python

  • Offered for Year: 2023/24
  • Module Leader(s): Dr Chris Graham
  • Owning School: Mathematics, Statistics and Physics
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System

Aims

To introduce the programming language Python and its application to mathematical problems. To promote familiarity with the environment for standard mathematical operations, and to work towards the ideas of coding user-defined functions and scripts, and further towards programming aimed at solving more substantial problems.

To promote independent thinking and critical appraisal by linking the computational experience to the tackling of unfamiliar problems that have not been directly demonstrated to them and which can be formulated mathematically.

Module summary

Computing methods are of great use in a wide range of applications of pure and applied mathematics, as well as statistics. This module will introduce and develop familiarity with mathematical computing, relate this to problem solving techniques based on independent thinking, and develop the ability to apply such methods independently, towards specific goals in mathematical study and applications.

Outline Of Syllabus

Use of Python for mathematical computing. Getting started, input and output, data types, plotting and simple calculations, control statements, functions, classes. An introduction to numerical methods.

Individual problems based on existing mathematical knowledge (such as calculus, sequences and series, single value functions, curve sketching and simple numerical analysis, linear algebra, matrix manipulations, permutations and combinations).

Mathematical problems and puzzles from logic, number theory, geometry, algebra, strategy.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture111:0011:00Formal Lectures
Guided Independent StudyAssessment preparation and completion12:002:00Class Test
Guided Independent StudyAssessment preparation and completion211:0021:00In course assessment preparation
Scheduled Learning And Teaching ActivitiesLecture102:0020:00Computer cluster practical sessions
Guided Independent StudyIndependent study461:0046:00Preparation time for lectures, background reading, coursework review
Total100:00
Teaching Rationale And Relationship

The teaching methods are appropriate to allow students to develop a wide range of skills, from understanding basic concepts and facts to higher-order thinking. Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Material will be available to tackle asynchronously following each lecture, with a practical which gives a chance for individual support.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Digital Examination1201M70Digital Examination (week 11)
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 format of the test will enable students to reliably demonstrate their own knowledge, understanding and application of learning outcomes. The assurance of academic integrity forms a necessary part of the programme accreditation.

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