72 hours (4 months)
3 modules + 1 final project
German or English
Certificate of completion
Chapter 1 – The Data Types
In this chapter you will navigate through our programming environment
– the Data Lab – for the first time and execute your first code commands.
You will learn what data or text represents in Python. Using a set of rules,
you will learn how to create, assign and test data in variables. You will then
learn how to read out common error messages and practice how to use
them productively in your day-to-day work. You will also learn basic Python
standard functions, such as type() or str() and use them in application
examples. After you‘ve learned about the if statement and can use it to
control the flow of your code with conditions, you‘ll finish the chapter with
the first part of a two-hour mini-project: You will program a user interface that
reacts flexibly to the user‘s input.
Chapter 2 – Flow control
In the second chapter you will work on two essential operations to make
your code even more flexible: You will learn about Vlists and for-loops. Lists
allow more flexibility in storing data and are a prerequisite for advanced
programming. You will learn to create them, read them and change them
purposefully. You will use lists to extend the functionality of your user
interface from the first chapter and complete the first mini-project. Afterwards
you will work with for-loops, which you can use to automatically execute your
code several times and level up your programming.
Chapter 3 – Functions, Modules and Methods
In the third chapter, you will round off your programming skills in Python
and learn some advanced techniques. These include functions and
methods. You learn how to define your own functions to structure your
code better. You will also combine the individual programming elements
such as conditions, loops and functions in programs. You will use various
methods and learn how to import Python modules correctly and how
to ensure functionality as a whole. Linked to this you will learn how
to import and export data as a simple test. In a one-hour mini-project
involving telephone data, you will consolidate what you have learned in
Chapter 4 – Python Applications
In the fourth chapter, you will recap content from chapters 1-3 and round
it off with additional material. You‘ll learn what dictionaries are and how
they can make your code more efficient. You will get to know complex
data structures that you will need for your final project. In a four-hour
hands-on project to create a complex user interface for automatically
processing customer requests, you will need to bring together everything
you learned in the previous chapters.
Chapter 1: Advanced Python:
In the introductory chapter, you‘ll review the most important content from the
previous module before learning a series of concepts that will catapult you to the
next level of programming with Python. You will take a deeper look at defining
functions and learn about default values, type hints and assert statements.
Afterwards, you will be able to use functions even more effectively as tools
for your projects. You will also cover the concepts of list comprehension and
dictionary comprehension to create lists and dictionaries efficiently. At the end
of the chapter you will learn how to adapt your code to the industry standard
PEP8 with layout and structure.
Chapter 2 – OOP Basics
In the second chapter you will learn what OOP is, which program principles are
based on it, and which conclusions you can draw from it, using simple examples.
In the main part of the chapter you explore how classes and attributes are
defined and used. You will use examples to examine instance methods and how
to use them and define them 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 intermediate
project and repeat the exercises from the chapter.
Chapter 3 – Inheritance and Composition
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 used in the
reusability of data from parent to child classes, compensating for data loss.
Finally, we will provide you with the most important best practices for unit tests,
so that you can detect errors in your code before your users find them.
Chapter 4 – Advanced OOP
In the fourth chapter you will deal with more advanced terms of objectoriented programming,
which will accompany you in your daily work. You
will study how programs and modules differ 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 can be used with __str_() and _repr_().
Based on this, you will learn about the options for representation operator
overloading offers as well as other important methods from the Python
Standard Library and then apply the learned content in a company-relevant
Chapter 5 – OOP Applications
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 to a popular data science
library that enables further uses for machine learning and data or text
analytics. The second project deals with programming your own blockchain,
where you will learn more about the underlying concepts. By the end of
Module 2, you‘ll be equipped to apply OOP in the corporate world.
As part of the final project, you will expand on what you learned in
the Python Basics and Object-Oriented Programming modules and
independently program a password manager. To do this, you will set up a
programming environment and, using a terminal, fill your file with records
that create a set of rules that configure the password manager.
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.)