Advanced Modeling of Physics and Engineering Problems Using Python Programming Language

Garant předmětu:

Václav Nežerka

Lecturer:

Václav Nežerka

Tutor:

Supervisor:

Department of Physics

Synopsis:

The aim of the course is to provide students with a deeper insight into advanced modeling of selected realistic physical and engineering problems using modern tools for mathematical description and numerical solutions of these problems. The elegant and easy-to-learn Python programming language can be used for this purpose. Although the course does not aim to provide a comprehensive introduction to this programming language, prior knowledge of it is unnecessary. Students will be given manuals with the basic commands and algorithms of the Python programming language. They will be introduced in regular lectures to (1) algorithmization of physical problems (5 hours), (2) numerical solution of complex equations (3 hours), (3) simulations (6 hours), (4) statistical modeling (4 hours), and (5) elementary machine learning (8 hours). Students will also be encouraged to apply the knowledge gained to their own work and projects.

Requirements:

None

Syllabus of lectures:

The curriculum will reflect the progress and needs of the students. The rough skeleton is as follows: (1) algorithmization of physics problems (5 hours), (2) numerical solutions of complex equations (3 hours), (3) simulation (6 hours), (4) statistical modeling (4 hours), and (5) fundamentals of machine learning (8 hours).

Syllabus of tutorials:

The same as for lectures.

Study Objective:

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

Study materials:

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

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

Instructional videos, articles, and custom materials provided by the instructor.

Note:

Time-table for winter semester 2024/2025:

Time-table is not available yet

Time-table for summer semester 2024/2025:

Time-table is not available yet

The course is a part of the following study plans: