course-E375004.md

Python for Scientific Computations and Control

Codenames: E375004, 2375004

1. Python Basics 1 - installation, IDEs, data types

   • lecture + lab
   • task: NO TASK this week, however make sure your Interpreter + IDE is working and you know how to operate it
   • responsible person: [email protected]

2. Python Basics 2 - for, while, if, functions

   • study Lecture
   • task: Lab task 1
   • responsible person: [email protected]

3. Python Basics 3 - functions, classes

   • study any introduction to Python classes, for example: W3Schools (easy to understand) or Python docs (more detailed)
   • study Lecture
   • task Lab task 2
   • responsible person: [email protected]

4. Game like simulations - Pygame

   • study the following example:Lecture - detail explanation in video
     • you cannot run in jupyter - use console or any IDE
     • you need pygame - it can be installed via pip
     • the example is quite complex, but it consists only from concepts you already know. Thus you should understand it pretty easily.
   • study the another example:Lecture
   • task: Lab task 3
   • responsible person: [email protected]

5. Html parsing, webscraping and server aplications

   • You will need following libraries (all instalable via pip): Beautifulsoup, requests.

   • What you should know before (general knowledge / internet basics):

     • HTTP protocol
     • JSON
     • HTML

     You need only basic knowledge of these (elementary/high school level).

   • Lecture materials:

     • Simple http server, in case of need use additional external resources (optional): https://www.youtube.com/watch?v=hFNZ6kdBgO0
     • Python http requests, the best additional resources is this external documentation: https://requests.readthedocs.io/en/master/
     • HTML and JSON parsing (you do not need to understand it fully, focus on work with JSON)

   • task: Lab task 4

   • responsible person: [email protected]

6. Flask applications (with jinja and WTForms)

7. NumPy and matplotlib

8. Pandas and plotly - Data processing and visualization

9. Multithreading

10. Optimisation - Introduction and Linear Programming

11. Artificial Intelligence - Part One

12. Artificial Intelligence - Part Two