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Python Programming

Importing, processing and storing data

Many office work processes can be automated as part of the digitalization process, reducing employees’ workloads and increasing productivity at the same time. Basic programming knowledge can often be enough to automate processes in your day-to-day work. StackFuel has developed a training course in which the basics of programming with Python are taught, thus providing participants with tools to automate their own work processes.

Target group

The course is suitable for anyone who's work is predominantly digital, but who did not study IT and a related subject. You should have an interest in technology.

Learning object

The goal of this hands-on course is to learn the basics of the free programming language Python and commonly-used libraries for importing, processing and storing local data.

Conditions for participation

No previous programming knowledge is required for the Python Programming course. You will develop these skills in the course. However, you should be a frequent computer user, and be familiar with common software.

Training type

FastTrack Online course
Standard Part-time online course to fit around your work

Total duration:

FastTrack Total duration: 1 Week (fulltime)
Standard Total duration: 4 Weeks (fulltime)



Next start dates


Standard 01.06.2020
Standard 06.07.2020
Standard 22.03.2021
Standard 19.04.2021

Contact and consultation


Tel: +49 (0) 30 6800 9503

Training formats

Python Programming Python Programming

Hands-on learning environment

Participants learn using current technologies and the latest Python libraries.

Advanced technology stack

Our trainings make use of real data sets as well as industry business cases to create hands-on Learning scenarios.


Participants have access to all the computing power they need to complete the course.

Innovative Data Lab

The course takes place in your browser, you don’t need to install any special software.


Module 1

Data types

Represent data as numbers or text in Python

Save data in variables and lists

Create, read and change lists

Read error messages and use them productively

Module 2

Data manipulation

Use standard Python functions like len() or sum()

Methods of text and list data types, e.g. str.format () or list.append()

Represent truth values ​​as bool and define them with comparison operators

Two-hour mini-project with car data to consolidate the learning content

Module 3

Flow control

Write for loops and link them to conditions

Write functions yourself and check how they work

Import python modules

Read data in as simple text and export it again

four-hour final project for workplace automationOne-hour mini project with telephone data to consolidate the learning content

Module 4

Deepening of the concepts and final project


List comprehension

Complex data structures

Numpy arrays

Four-hour final project for workplace automation

Starting dates

01.06 - 31.01.2021Length: 4 Weeks
06.07 - 06.09.2020Length: 4 Weeks
22.03 - 04.10.2020Length: 4 Weeks


Request the course curriculum for more detail about the course material!

Python Programming
Python Programming

Flexible course formats

StackFuel has developed various training formats to meet the diverse requirements of a modern working environment. Our regular part-time courses are designed specifically with company employees in mind, and combine professional development and in-depth skill development with day-to-day work. Our FastTrack courses are tailored specifically toward our participants and customers who would like to take part in our courses more quickly on a part-time or full-time basis. The time spent on our courses each week as part of our FastTrack formats is therefore more concentrated, and you will ready for the job role of Data Analyst or Data Scientist more quickly.


StackFuel's specialist courses follow a practical approach that trains employees for the job roles of the future and gives them the necessary skills to create real added value from data. This is also reflected in the final project that the participants carry out and which our mentoring team, made up of educational data scientists, analyzes and evaluates. Participants receive a certificate based on an independent final project at the end of the course, which they can use in various social networks as well as privately, as proof of their newly acquired knowledge and skills. Our specialist Data Analyst (73598) Data Scientist (73597) courses are ZFU* tested and certified.

*The ZFU checks whether a course meets the requirements of the German Distance Learning Protection Act (Fernunterrichtschutzgesetz) and whether courses are suitable for distance learning in terms of their subject matter and didactics.

Python Programming
  • testimonial

    Alexander Groß

    Data Analyst at AIC Portaltechnik

    The Data Lab really offers added value, you notice instantly how the practical exercises are relevant to your work. The tasks were always clearly described and presented. So I always knew what to do. The course itself was a great experience!

  • testimonial

    Lutz Schneider

    Strategic buyer at Axel Springer SE

    The greatest added value for me was the courses practical relevance. Thanks to StackFuel, I can quickly put what I have learned into practice and adapt it for myself. This is the real learning success behind the online course.

  • testimonial

    Jaroslaw Wojciech Sulak

    Specialist for data analysis at IAV GmbH

    The online StackFuel course content was very hands on. There were a great deal of good examples and projects. I found it very interesting and instructive. My professional life has changed significantly since completing the course: Im now a data analysis specialist in my department.

  • testimonial

    Jenny Lindenau

    Head of Test Management at Bank Deutsches Kraftfahrzeuggewerbe GmbH

    The user-friendly and flexible Python Programming course has entirely changed my view on complex data structures. Thanks to the sustainable and well-designed learning approach, and the seamless use of learning content in the coding environment, I can now apply my new skills in my daily work of testing automation and process data more easily and efficiently.

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