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Courses
Artificial intelligence and data
AI and data are the engine of the future. In our e-learning courses, employees learn how they can use these technologies in a targeted manner to optimize processes and secure competitive advantages. At the same time, they acquire in-depth knowledge for responsible and risk-conscious use of these technologies.
Developing AI and Data Skills for Everyday Work
Using AI applications effectively starts with understanding their capabilities and limitations within one’s own area of responsibility. An AI training program for employees in the form of e-learning can be a good starting point here. The “ Content Collection ” combines courses on the practical use of generative AI—which, for example, creates text—with modules on data literacy.
You can develop these skills
- Classifying AI Applications: Identifying potential uses in everyday work and applying them to specific tasks.
- Formulating Prompts: Designing inputs for AI tools that are appropriate for the task and understanding the logic behind prompting.
- Creating Text with AI: Using AI to Support Professional Writing Tasks and Tailoring Content to the Target Audience.
- Understanding Data: Interpreting data, questioning misinterpretations, and learning about AI-powered analysis.
Here's how to combine courses into learning paths
Putting Generative AI to Practical Use: For employees who handle writing and knowledge-based tasks, the following sequence is recommended: “Using Artificial Intelligence in Everyday Work” → “Prompt Engineering” → “Writing Professional Texts with Artificial Intelligence.” This suggestion provides a path from an overview of AI applications to the formulation of prompts and a specific writing task. It can, for example, be incorporated into the rollout of approved AI applications within the company. The selection should be based on the actual tasks of the respective department.
Deepening Data Literacy: “Confidently Working with Data” → “Making Data-Driven Decisions” → “Analyzing Data with Artificial Intelligence” combines an understanding of data with interpretation and AI-supported analysis. This combination is ideal for employees who want to use data to make professional decisions. It places a different emphasis than the learning path for writing tasks.
As a supplementary application exercise, teams can test a company-approved use case using non-confidential sample data and critically evaluate the results. The suggested learning paths are intended to foster skill development; they are separate from any assessment of legal training requirements.
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