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 training 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
  • Target group

    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.

    Requirements for participation

  • Assessment
  • Basic knowledge of mathematics & statistics
    • Type

      Online course

    • Duration

      72 hours (4 months)

    • Structure

      3 modules + 1 final project

    • Level

      Entry level

    • Languages

      German or English

    • Completion

      Certificate of completion

    • Price

      € 4,990,00
      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.

    Modules

    Module 1: Python Basics

    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

    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.

    Module 2: Object-Oriented Programming

    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
    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
    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.

    Module 3: Final Project

    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.

    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.
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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.
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    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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