Introduction to Python

Introduction to the language and insight to the context of other programming languages, differences across operating systems, modules

Natural data types, python data model, fixed and variable types

Seminar work assignment

The remaining data types (List, tupple, dict…) and the construction of matrix considerations and data storage

Data types from basic modules (matrix, dataframe)

Logical operations, conditions, cycles

Cycles, exceptions, mathematical operations, basic modules and numpy

User-defined functions

Function parameters, function body, global and local function environment, lambda functions, recursive functions

Import and export of data, csv, json and other data formats

Data visualization and matplotlib, API and other graphics libraries

Creating your own module, analysis of default modules

Introduction to Object Oriented Programming (OOP)

Properties of OOP, examples of inheritance

Creating your own classes, creating your own exceptions in the context of OOP

Modules for linear and nonlinear optimization

Python as a tool for machine learning and an example of a neural network