Advanced Modeling of Physics and Engineering Problems Using Python Programming Language

The course is not on the list Without time-table
Code Completion Credits Range Language
D02MFPY_EN ZK 2P English
Garant předmětu:
Department of Physics

The aim of the course is to provide students with a deeper insight into problems of advanced modeling selected real physical and engineering tasks with the use of modern tools for mathematical description and numerical solution of such problems. For that purpose, it is handy to use the elegant and easy-to-learn Python programming language. Even though the course is not intended to provide a comprehensive introduction to Python, prior knowledge is not required. The students will be given handouts with basic Python commands and algorithms and during regular lectures will be introduced to (1) algorithmizing the physics problems (5 hours), (2) numerical solution of complex equations (3 hours), (3) simulations (6 hours), (4) statistical modeling (4 hours), and (5) basics of machine learning (8 hours). Students will be also encouraged to use the gained knowledge for their own work and projects and individual consultations.


Attendance in lectures

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 lecturer.

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-06-16
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