Last Call: AI and data science in the company – from raw data to insights

Many companies have an immense treasure trove of data about their own products, users, internal workflows and more. For a long time, the maxim was to collect as much data as possible; at some point it could eventually become helpful. However, these data collections are so extensive that a manual analysis would be extremely time-consuming. Artificial intelligence can help here by recognizing patterns and pre-structuring raw data in order to derive strategies from it. Our Classroom AI and Data Science in the company – from raw data to usable insights, teaches you how to develop data sources in a practical way and get from the first analyzes to a convincing data story.

In five consecutive sessions, participants learn the skills to use data strategically and establish data-driven decisions in the company. Our expert first establishes the necessary AI foundations. Building on this, he devotes himself to established frameworks, such as the ACHIEVE framework and the Impact vs Effort Matrix, in order to systematically evaluate and prioritize use cases. Below, participants will learn everything they need to know about data collection and processing. They use this to identify structured and unstructured data sources, conduct exploratory data analysis (EDA), and apply data cleansing techniques. Our expert also addresses ethical aspects of data analysis and shows how to recognize and avoid bias.

Using traditional analysis methods and AI to create a convincing data story

As the classroom progresses, participants learn the practical use of Python and Jupyter Notebooks to combine traditional analysis methods and modern AI tools to significantly accelerate work processes. Our expert is also dedicated to visualizing analysis results. He explains when static or interactive representations make sense and how to present complex data in an understandable way.

Finally, the focus is on storytelling with data in order to develop a convincing data story for different target groups, create a structured communication plan and design a focused mini-data strategy for a specific use case. With this knowledge, participants are able to establish sustainable and data-driven initiatives in the company. The dates of the sessions are:

• 06/03/26: Using artificial intelligence strategically – from buzzword to concrete use case
• 06/10/26: Exploratory data analysis (EDA) – identify data sources and ensure data quality
• 06/17/26: Data analysis with Python – Jupyter Notebooks, Pandas and ChatGPT as analysis tools
• 06/24/26: Data visualization with Python and Tableau – from analysis to meaningful dashboards
• 07/01/26: Communicate data analysis successfully – target group-oriented presentation and strategy planning

Practical and expert knowledge – live and for later

The sessions last four hours each and take place from 9 a.m. to 1 p.m. All participants can not only look forward to a lot of practice and interaction, but also have the opportunity to repeat and deepen what they have learned with all the recordings and materials afterwards. Questions are answered directly in the live chat and participants can also exchange ideas with each other on the topic. Subsequent access to the videos and exercise materials is included. Those interested can find further information and tickets on the classroom website.

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