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AI+ Data Practitioner™
Information becomes a resource – when you know how to process it. This training connects data handling with AI technologies and builds a practical foundation for analytical work in the digital world.
Key topics
- Structured data evaluation using modern AI methods.
- Automated workflows for efficient information processing.
- Using generative AI purposefully for analysis and structuring.
- Analytics, machine learning, and automation in practice.
- Ethical, secure, and quality-conscious handling of data.
Prerequisite
Anyone familiar with digital tools and interested in analytical processes will find an ideal starting point here.
Target group
Suitable for professionals in analysis, technology, and business – wherever decisions need to be grounded in solid data.
This course opens a clear path to AI-supported data expertise – practical, scalable, and directly aligned with modern professional demands.
course content
Data science essentials: introduction and overview
- Fundamentals and key concepts of data science
- Phases and process of a data science project
- Real-world examples and application areas
Statistics as the foundation for data analysis
- Core concepts and key metrics in statistics
- Foundations of probability theory
- Drawing conclusions from data
Understanding data: sources, types, and storage
- Overview of structured and unstructured data
- Internal and external data sources at a glance
- Storage formats and technologies for data projects
Coding for data work: Python and R in practice
- Python basics for data-driven tasks
- R as a tool for statistics and analysis
Preparing data: cleaning and transformation
- Identifying and replacing missing values
- Handling outliers and transforming data
EDA: exploring and understanding data
- Core principles of exploratory data analysis
- Making data visible: visualization methods
Generative AI: extracting insights from data
- Overview of generative AI tools
- Use cases for generative AI in analysis
Machine learning: fundamentals and algorithms
- Supervised learning: concepts and methods
- Unsupervised learning and its applications
- Clustering algorithms compared
- Identifying and implementing association rules
Going deeper: advanced machine learning
- Ensemble methods for more robust models
- Reducing complexity with dimensionality techniques
- Model optimization at an advanced level
Data-based decisions: methods and tools
- Fundamentals of data-based decision processes
- Open-source tools for analytical decisions
- Practical exercise: gaining insights from sales data
Data storytelling: presenting data persuasively
- The impact and importance of data storytelling
- Recognizing relevant use cases in a business context
- Turning numbers into stories
- Using visualizations that create impact
Final project: predicting employee turnover
- Getting to know the task and starting problem
- Collecting and preparing datasets for analysis
- Carrying out analysis and model development
- Preparing and communicating results clearly
Optional module: AI agents in data work
- Structure and functioning of AI agents
- Real-world examples from practical applications
- Hands-on: applying AI agents yourself
Up to 100% funding for your continuing education
Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.
Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.
