Design Principles for Software Development with Object-Oriented Programming

Python – Focus Object-Oriented Programming

Course description

With the Python – Focus Object-Oriented Programming course, you will bring your Python skills to the next level. It teaches you the principles and best practices of object-oriented programming so that you can implement your software projects even more efficiently.

In this training you will learn

  • Process functions and lists in Python
  • Working with selected OOP classes & attributes
  • Interactive interim project on best practice handling of work processes
  • Object-oriented programming focusing on classes and attributes
  • Using inheritance to reuse code
  • Advanced functions for simplifying classes
  • Target group

    The mid level course 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

    No prior knowledge or programming skills are required for the course.
    • Type

      Online course

    • Duration

      4 Weeks

    • Structure

      5 chapters + 2 exercise projects

    • Level

      Mid level

    • Languages

      German or English

    • Completion

      Certificate of completion

    • Price

      incl. VAT

    That awaits you

    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.


    Chapter 1 – Advanced Python

    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


    Chapter 2 – OOP Basics

    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.

    Chapter 3 – OOP Concepts

    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.

    Chapter 4 – Advanced OOP

    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.

    Chapter 5 – 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‘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.

    Download the curriculum now.​

    Learning environment

    Train online in the browser in our interactive learning platform.

    StackFuel offers you an innovative learning environment with which you can develop your data skills in the most effective way – interactively and with real practical tasks. Learn to program in our data lab and develop algorithms and automations with real data sets from the industry. Convince yourself now and benefit from 80% practice in our training courses.
    Why StackFuel

    We are your strategic learning partner - including mentoring and support.

    Whether you are an employee, unemployed or a manager – we will develop you into a data talent with our fundable further training and retraining courses that are suitable for every department and every career level. We ensure your learning success with our dedicated mentoring team and always stay on the ball with you. Our practical tasks and projects make you fit for dealing with the latest technologies and applications.
    100% FOR YOU

    Personalize your learning experience.

    Non-binding trial week
    With our non-binding trial week you get an insight into your desired training. Then you have the choice: either you decide on the training or you look for another one that suits you even better.
    Individual course modules
    With us you can put together the modules of your further training tailored to your needs. Whether business intelligence, data analytics, data science or programming: use your time optimally to build up expert knowledge and develop your skills individually.

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    Payment options

    Find your suitable financing.

    With an education voucher, you can have your further education financed 100% by the job center or the employment agency if you are currently registered as unemployed or looking for a job.
    If you are employed, you can have your employer partially or fully finance your further training through the Qualification Opportunities Act – regardless of qualification, age and company size.
    If you are currently enrolled at a university or college in Germany, you can complete our courses at a 50% discount.
    Use our installment plan to spread the cost of your training over several months and maintain your financial flexibility.
    Pay safely and easily after your training by having us issue you an invoice.
    Our FAQ

    The most important questions at a glance.

    The need 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 specialists were advertised in Germany. Above all, the demand for data and AI experts continues to increase enormously. But a decision for a data career is so much more than just a secure future decision! As a data expert, you deal with strong, socially relevant topics, and at the same time you are a tech professional and communicative and creative. The job is varied, can be combined with most other jobs and offers an attractive salary. And the most important thing: It can be learned with us without fail!
    Yes, after successfully completing the training, you will receive a certificate of completion from us that you can show when you apply. Data Analysts and Data Scientists are desperately needed in many economic sectors. Even without relevant professional experience, your chances of getting an entry-level job are good. In addition, there are analysts in almost every industry, they have different job titles, but the skills you need are the same as those of a data analyst or data scientist.
    No, the training is flexible in terms of time and designed to be part-time. You can pursue your profession without restrictions and can plan your learning times at the time that suits you best. If you suddenly have more time available, you are welcome to contact us by e-mail and we will activate the learning content for the part-time version in your account. In this variant, you can complete the training in just four weeks. If you notice that you need more time, you can still complete the content in the normal time.

    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.)

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