Course detail

Programming in Python

FSI-TPYAcad. year: 2024/2025

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

Mode of study

Not applicable.

Guarantor

doc. Ing. Miroslav Bartošík, Ph.D.

Department

Institute of Physical Engineering (ÚFI)

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.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Pilgrim Mark, Ponořme se do Python(u) 3, CZ.NIC, 2012 (CS)
Summerfeld Mark, Python 3, výukový kurz, Computer Press, 2021. (CS)

Recommended reading

Not applicable.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme B-FIN-P Bachelor's 2 year of study, winter semester, compulsory-optional

  • Programme C-AKR-P Lifelong learning

    specialization CZS , 1 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hod., 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 hod., 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

Elearning

eLearning: currently opened course