5 chapters + 2 exercise projects
German or English
Certificate of completion
In the first chapter you will look at defining functions in more detail and learn
about default values, type hints and assert statements. Afterwards, you can
use functions even more effectively as tools for your projects. You will work
with the concepts of list comprehension and dictionary comprehension to
efficiently create lists and dictionaries. At the end of the chapter you will learn
how to adapt your code to the PEP8 industry standard by means of layout and
In the second chapter, you will learn what OOP is, which programming
principles are based on it, and which 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. You will use examples to examine
instance methods, how they’re used and defined with method chaining.
You‘ll learn what the self keyword is, as well as how to distinguish debugging
from class definitions. Finally, you will test your previous knowledge in an
interactive interim project and repeat the exercises from the chapter.
In the third chapter, you will learn what inheritance and composition are and
how to use these concepts in use cases. In addition to simple inheritance, you
will also learn more advanced methods such as inheritance hierarchy and
multiple inheritance. In doing so, you‘ll practice deep inheritance methods
to make data reusable from parent to child classes, to compensate for data
loss. Finally, you will learn the most important best practices for unit testing in
order to detect errors in your code before your users find them.
In the fourth chapter, you will deal with more advanced concepts of
object-oriented programming, which you will use in your daily work.
You will study the difference between programs and modules and
what role __main__ plays. You will learn what decorators are and how
to use property decorators optimally. You will look at static and class
methods and what special methods and class representations you
can use with __str_() and _repr_(). Based on this, you will learn about
the possibilities offered by operator overloading as well as other
important methods from the Python Standard Library and then apply
what you have learned in a business-relevant interim project.
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‘ll build your own interface for a
popular data science library that makes it possible to apply machine
learning or data or text analytics methods. The second project deals
with programming your own blockchain, where you will learn more
about the underlying concepts.
Yes, our online training courses should offer you the greatest possible flexibility. Basically, we recommend planning six to eight hours a week for studying. When you want to schedule this time is up to you and is not prescribed by us. In our career paths, the Data Analyst and Data Scientist course, we offer you live webinars where you can ask our mentors questions, but you don’t have to attend if it doesn’t fit into your schedule.
(Participants in our funded training courses are an exception. They have to attend a fixed number of hours per week and are obliged to take part in the live webinars.)