Python for physical modeling

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Physics

Synopsis:

The aim of the course is to teach students how to implement computational algorithms to solve engineering calculations using a modern programming language (Python). Ignorance of programming is becoming a huge handicap for graduates both in finding jobs and entering PhD studies. Translating problems into computer code forces students to think analytically and optimize computational procedures. The development and use of programmed algorithms effectively combine the interpretation of theoretical physics principles with their direct application for computation and optimization. Prior programming experience or knowledge of Python is not a prerequisite for enrolling and completing the course.

Requirements:

Active participation in lessons

Syllabus of lectures:

The curriculum will reflect the progress and needs of the students. The rough skeleton is as follows: (1) introduction to the Python programming language, (2) algorithmization of physics problems, (3) numerical solutions of equations, (4) simulation, (5) statistical modeling, and (6) fundamentals of machine learning.

Syllabus of tutorials:

Similar to the lectures.

Study Objective:

The aim of the course will be to introduce students to programming and algorithmization tasks.

Study materials:

[1] Ryan Turner, Python Programming, Nelly B.L. International Consulting LTD., 2020 (ISBN: 1647710715)

[2] Jesse M. Kinder, Philip Nelson, Student's Guide to Python for Physical Modeling, Princeton University Press, 2018 (ISBN: 9780691180571)

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: