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Python - Focus Object-Oriented Programming

Design principles for software development with object-oriented programming

Certificate of completion
Full time/part time
German, English
Course description

With the training Python - Focus Object-Oriented Programming you deepen your Python knowledge and bring it to the next level.

You will learn the most important design principles and best practices of object-oriented programming, so that you can implement your software projects even faster and more efficiently.

In this training you will learn
Advanced Python
OOP Basics
OOP Aplications
  • Process functions and lists in Python
  • Working with selected classes & attributes of OOP
  • Interactive interim project on best practice handling of work processes
  • Object-oriented programming (OOP) with focus on classes and attributes
  • Use inheritances for code reusability
  • Advanced functions for simplifying classes

Target group

The advanced training is designed for those who already have experience with Python and want to use the programming language effectively in a professional context.

Requirements for participation

Basic programming knowledge in Python is required for the training.


Advanced Python

In the first chapter you will take a deeper look at function definition and learn about default values, type hints and assert statements. Afterwards you can use functions even better as tools for your projects. You will work with the terms list comprehension and dictionary comprehension for the efficient creation of lists and dictionaries. At the end of the chapter, you will learn how to adapt your code to the industry standard PEP8 by means of layout and structure.

OOP Basics

In the second chapter, you'll learn what OOP is, what programming principles are based on it, and what conclusions you can draw from it, using simple examples. In the main part of the chapter you will explore how classes and attributes are defined and used. Using examples, you will examine instance methods and their use and definition with method chaining. You will learn what the self keyword is and how to distinguish debugging from class definitions. Finally, you will test your knowledge in an interactive intermediate project and repeat the exercises from the chapter.

OOP Concepts

In the third chapter, you'll learn what inheritance and composition are and how to use these concepts in use cases. In addition to simple inheritance, you'll also learn more advanced methods such as inheritance hierarchy and multiple inheritance. You'll practice deep inheritance methods that are used when reusing data from parent to child classes, compensating for data loss. Finally, you'll learn the most important unit testing best practices to help you find bugs in your code before your users find them.

Advanced OOP

In the fourth chapter you will deal with more advanced concepts of object-oriented programming, which will accompany you in your everyday work. You will study how programs and modules differ and what role object __main__ plays a role in this. You will learn what decorators are and how to use property decorators optimally. You will look at static and class methods and which special methods and class representations are possible with __ str__ () and __repr__ () can be used. Based on this, you will learn about the representation options of operator overloading and other important methods from the Python Standard Library and then apply the learned content in a company-relevant interim project.

OOP Applications & Final Projects

In the fifth chapter, you will demonstrate your knowledge in two larger projects that represent classic use cases of object-oriented programming. In the first project, you will build your own interface to a popular data science library that enables further uses for machine learning or data or text analysis. The second project deals with programming your own blockchain, where you will learn the underlying concepts in more detail.

The StackFuel Data Lab offers me real added value. Here you can feel the practical relevance particularly well. The tasks were always clearly described and presented. So I always knew what I had to do. The training itself was a great experience!
Alexander Gross
Data Analyst at AIC Portaltechnik
The greatest added value for me is the practical relevance. Thanks to StackFuel, I can quickly implement what I've learned and adapt it for myself. That is the real learning success behind the online trainings.
Lutz Schneider
Strategic IT Buyer at Axel Springer SE
The content of StackFuel's online training was very practical. There were many good examples and projects. I found that very interesting and instructive. Since the training, my everyday professional life has changed significantly: I am now a data analytics specialist in my department.
Jaroslaw Wojciech Sulak
Specialist for data analysis at IAV GmbH
The user-friendly and flexible Python programming training has completely changed my view of complex data structures. Thanks to the sustainable and well thought-out learning concept as well as the seamless application of the learning content in the development environment, I can now implement the newly learned knowledge in my everyday job in test automation in greater depth and process data more easily and efficiently since then.
Jenny Lindenau
Technical Manager Test Management at Bank Deutsches Kraftfahrzeuggewerbe GmbH

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1.990,00 *
(incl. VAT)
0 € with education voucher