Storytelling with Python: Transforming Code into Engaging Stories

 150,00

Plus 20% VAT

Note for groups: If you are buying this product for multiple participants, you will be able to assign licenses after completing the order. Please select “Group” and the number of seats you require.



  • Scope: 1,5h online training on storytelling with Python
  • Level: All
  • Format: Online

This training is available on demand. Please contact Rosina Preis via rosina.preis@eitmanufacturing.eu for further information.

Discover the possibilities of programming with our interactive online training "Storytelling with Python: Transforming Code into Engaging Stories". Join us for an immersive session where we unravel the narrative potential of Python, empowering you to transform code into compelling stories. Through real-world examples, hands-on exercises, and expert insights, this online training is meticulously designed to enhance your coding skills, ensuring you leave with a comprehensive understanding of how to weave storytelling elements into your Python programs. Immerse yourself in an interactive experience that will revolutionize your approach to programming as a form of creative expression. This training is part of the learning path "Industrial Data Science" and may be combined with other sessions. Main learning outcomes:

  • Demonstrate proficiency in crafting Python code with a narrative structure, making programs more readable and engaging.
  • Gain a deep understanding of the principles of storytelling in programming, including the use of comments, variable naming, and code organization.
  • Learn to employ Python's documentation and docstring features to enhance code communication and collaboration within a team.
  • Develop the skills to use visualizations and data representations to tell a compelling story through Python programs.
  • Apply storytelling techniques to real-world coding challenges, equipping you with the ability to communicate complex ideas in a clear and concise manner.

Who is this training for:

  • Business analysts
  • Industrial, mechanical and civil engineering students and alumni
  • Practitioners without knowledge of data science