Python for Scientific Computations and Control

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Instrumentation and Control Engineering

Synopsis:

The course covers Python basics, basics of object-oriented programming, and advanced topics such as data processing, mechanical system simulations, parallel programming, and artificial intelligence. It is structured into weekly modules focusing on different Python applications using well-known libraries like NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Requests and FastAPI.

Requirements:

Syllabus of lectures:

1. Getting acquainted with the Python environment. Installation, IDEs, basic syntax, data types, functions.

2. Python and object-oriented programming: classes and objects, methods, attributes, inheritance, polymorphism, magic methods.

3. Python for scientific computing using the NumPy, SciPy libraries - linear algebra, solving differential equations. Time series visualization using the Matplotlib library.

4. Working with data using the Pandas library. Loading data from a file, preprocessing, data operations such as sorting, filtering, basic statistics.

5. Simulation of mechanical systems.

6. Control of mechanical systems.

7. Optimization – linear and quadratic programming.

8. Parallel programming (multithreading).

9. Introduction to artificial intelligence (genetic algorithms, fuzzy systems, perceptron).

10. Artificial intelligence using the TensorFlow library - neural networks (MLP, convolutional neural networks, self-organizing maps).

11. Fundamentals of web application development: Databases, requests, API.

12.,13. Basics of user interface development.

Syllabus of tutorials:

Study Objective:

Study materials:

https://github.com/CVUT-FS-12110/Python-for-Scientific-Computations-and-Control/tree/master

https://moodle-vyuka.cvut.cz/

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: