470-2701/01 – Scientific calculations in Python (VVP)
Gurantor department | Department of Applied Mathematics | Credits | 5 |
Subject guarantor | Ing. Jan Kracík, Ph.D. | Subject version guarantor | Ing. Jan Kracík, Ph.D. |
Study level | undergraduate or graduate | Requirement | Compulsory |
Year | 1 | Semester | summer |
| | Study language | Czech |
Year of introduction | 2022/2023 | Year of cancellation | |
Intended for the faculties | FEI | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
In Python programming language, Computational and Applied Mathematics students get a freely available tool with a wide range of applications.
Teaching methods
Lectures
Tutorials
Project work
Summary
Compulsory literature:
https://docs.python.org/3/
https://numpy.org/doc/stable/
https://scipy.github.io/devdocs/index.html
Recommended literature:
https://docs.github.com/en
https://docs.jupyter.org/en/latest/
Way of continuous check of knowledge in the course of semester
Semestral project
E-learning
Other requirements
No other requirements are imposed on the student.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Basics
- basic data types, containers
- algebraic operations, basic functions
- mutable and immutable types
- program runtime control, loops
- functions
- classes
- namespaces, variable validity scope
- packages, modules
- debugging, profiling
Development Environment, tools
- IDE
- Jupyter-lab
- GitHub
- pip
Habits
- comments
- version control
- DRY
Libraries for scientific computing
- numpy
◦ array, indexing, cuts, completions
◦ vector operations
- matplotlib
- scipy, sympy
Advanced
- Extending Python with C
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction