Qualification for the Job Role of a Python Programmer

Python Programmer – Focus Object-Oriented Programming

Course description

With the certified online course to become a Python Programmer, you will enter the world of software development with Python. You will learn the basics of the Python programming language and familiarize yourself with the most important programming concepts such as variables, types, functions and methods. Based on this, you will independently develop and extend classes and modules. You will perform unit tests and ensure the functionality of your code. You will work with the popular Python Standard Library and explore advanced concepts of object-oriented programming such as inheritance and composition. You will finish the program with a business-relevant final project to configure a password manager, and upon successful completion of the career path, you will qualify for a job role as a Python Programmer, Python Developer, or Software Developer.

In this course you will learn:  

  • Processing data and text in Python
  • Working with selected Python libraries
  • Practice project to automate work processes
  • Object-oriented programming (OOP) with a focus on classes and attributes
  • Using inheritances for code reusability
  • Get to know more advanced functions for simplifying classes
  • Final project to configure a password manager
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    Target Audience  

    The Python Programmer course is suitable for anyone who wants to learn Python as a programming language and use it professionally. You should have an enthusiasm for logical thinking and solving complex problems. The further training is suitable for career changers and the perfect entry into software development to become a Python developer, software developer or data scientist.

    Prerequisites for participation 

  • Assessment
  • Basic knowledge of mathematics & statistics
  • Online course
    Part-time: 4 months
    Full-time: 10 weeks
    3 modules + 1 final project
    Entry level
    Certificate of completion

    Every 1-2 months

    What to Expect

    Course Overview

    Feature 1

    From data literacy courses for beginners with no prior knowledge to retraining in data science and AI for domain experts - we cover all career levels.

    Feature 2

    Learning by doing is very important to us - we focus 90% on interactive formats, real business cases and coding challenges.

    Feature 3

    We guarantee your learning success - with weekly webinars, support via email, telephone or forum and standardised off- and onboarding.

    Feature 1

    From data literacy courses for beginners with no prior knowledge to retraining in data science and AI for domain experts - we cover all career levels.

    Feature 2

    Learning by doing is very important to us - we focus 90% on interactive formats, real business cases and coding challenges.

    Feature 3

    We guarantee your learning success - with weekly webinars, support via email, telephone or forum and standardised off- and onboarding.


    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
    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
    the chapter.

    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
    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
    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
    . 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
    offers as well as other important methods from the Python
    Standard Library and then apply the learned content in a company-relevant
    interim project.

    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
    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.
    Module 3: Final Project

    Download the­ curriculum now.


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    Our FAQ

    The most important questions at a glance.

    The demand for data experts is high. Around 4 million data experts will be needed in Europe by 2025. And in 2021 alone, more than 80,000 positions for IT professionals have already been advertised in Germany. Above all, the demand for data and AI experts continues to grow enormously.

    But a decision for a career in data is so much more than just a safe decision for the future! As a data expert, you’ll deal with powerful, socially relevant topics, be a tech professional and be communicative and creative at the same time. The profession is varied, can be combined with most other professions and offers an attractive salary. And most importantly: you can learn the kills you need with us!

    Yes, after successfully completing the course, you will receive a certificate of completion from us that you can show in your job applications. Data Analysts and Data Scientists are desperately needed in many business sectors. Even without relevant work experience, your chances of finding an entry-level job are good. In addition, there are analysts in almost every industry, who may have different job titles, but the skills you need are the same as those of a data analyst or data scientist.

    No, the course is designed to be flexible in terms of time and can fit around your job. You can pursue your profession without restrictions and can schedule your learning times as they best suit you. If you suddenly have more time available, you can contact us by email and we’ll activate the learning content for the more intensive version in your account. In this version you can complete the training within just four weeks. If you find that you need more time, you can still complete the content in the regular time.

    Yes, our online training courses are designed to offer you the greatest possible flexibility. Basically, we recommend that you plan six to eight hours per week for learning. When you schedule this time is up to you and is not prescribed by us. In our career paths, the Data Analyst and Data Scientist courses, we offer live webinars where you can ask our mentors questions, but you don’t have to attend if it doesn’t fit your schedule.

    (This does not apply to participants in our funded training courses. They have to attend a fixed number of hours per week and are obliged to participate in the live webinars).

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