Course detail

Programming in Python

FSI-TPY Acad. year: 2024/2025 Winter semester

This course covers the basics of the Python programming language, with a focus on its practical applications in engineering.

Language of instruction

Czech

Number of ECTS credits

2

Supervisor

doc. Ing. Miroslav Bartošík, Ph.D.

Department

Institute of Physical Engineering

Entry knowledge

Basic computer literacy at a high school level is assumed.

Rules for evaluation and completion of the course

Attendance at lectures is encouraged, and participation in exercises is mandatory. Classes follow a weekly schedule, and credit is awarded based on completing a script simulating a simple physics task.

Aims

The goal is to develop proficiency in using Python for engineering practice.

The study programmes with the given course

Programme B-FIN-P: Physical Engineering and Nanotechnology, Bachelor's, compulsory-optional

Programme C-AKR-P: , Lifelong learning
specialization CZS: , elective

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Ing. Jakub Zlámal, Ph.D.

Syllabus

  1. Introduction to Python
  2. Version control with Git
  3. Lists, tuples, dictionaries
  4. Numpy for vectors and matrices, matrix operations, and index expressions
  5. Control structures
  6. Matplotlib for plotting points, curves, surfaces, and data plots
  7. Input and output of data, including working with text and regular expressions
  8. Functions, including built-in and user-defined functions, parameter types, and recursion
  9. Numerical derivation, integration, and ODR solutions
  10. Introduction to object-oriented programming
  11. Application of the object-oriented approach to solving n-body problems
  12. Optimization tasks
  13. Overview of Python packages

Computer-assisted exercise

13 hours, compulsory

Teacher / Lecturer

Ing. Jakub Zlámal, Ph.D.

Syllabus

  1. Installing Python – Anaconda and ChatGPT
  2. Version control using GitHub
  3. Lists, tuples, dictionaries
  4. Numpy for vectors and matrices, matrix operations, and index expressions
  5. Control structures
  6. Matplotlib for plotting points, curves, surfaces, and data plots
  7. Input and output of data, including working with text and regular expressions
  8. Functions, including built-in and user-defined functions, parameter types, and recursion
  9. Numerical derivation, integration, and ODR solutions
  10. Application of the object-oriented approach to solving n-body problems
  11. Optimization tasks
  12. Semester project
  13. Submission of semester project