Last modified: 31 May 2022 13:05
This course introduces mathematical and computational methods. One half is an introduction to programming starting at basics such as variables, loops and conditional statements. This course part is taught in Python, with an emphasis on modern programming concepts and data analysis skills. The other half, taught concurrently, consists of advanced mathematical methods using examples from Physics; for example multivariable calculus and Maxwell's equations, or ODE and partial differential equations in classical and quantum mechanics. There will be a one week career strategies module at the end of the course.
|Session||First Sub Session||Credit Points||15 credits (7.5 ECTS credits)|
This course will introduce computing skills including programming and numerical analysis methods and key mathematical skills commensurate with those required by other honours courses such as Electricity and Magnetism. The course is divided into two halves. In the first half, students will develop programming and numerical analysis skills. Using Python, they will first learn the basics of programming, including loops, conditions and functions. Using this basis, they will then apply numerical algorithms to solve differential equations, eigenvalue problems and integration, and learn how to analyse and visualise data. An individual programming project concludes this part. In the second half students will revise and develop key mathematical skills including their ability to cope with vector calculus, differential and integral equations and linear algebra. Topics such as Stokes’s, Green’s and Gauss’s theorems will be explored and applications discussed.
Information on contact teaching time is available from the course guide.
Exercise Sheets (20%)
3 x Home assignments (50%)
Alternative Resit Arrangements
Online test 1 (50%)
Online test 2 (50%)
There are no assessments for this course.
|Knowledge Level||Thinking Skill||Outcome|
|Factual||Remember||ILO’s for this course are available in the course guide.|