Contents
Module 1
Introduction
- Terminology around data and artificial intelligence.
- Why data is the key to successful AI projects.
Data types and formats
- What types of data are there?
- Variable types and scale levels.
- Unstructured data, semi-structured data and structured data.
Data management for AI projects
- Supervised vs. unsupervised learning.
- What are the data and data volume requirements for the use of AI?
- How to recognize poor data quality.
- Ensure data quality in productive AI applications.
Module 2
Storage of data
- Types of databases.
- Overview of Data Lake and Data Warehouse.
- Advantages and disadvantages of data storage and processing in the cloud vs. on premise.
- External data sources as a supplement to internal data.
Data security
- Personal data and GDPR.
- How to ensure data sovereignty.
- EU AI Act.
Competencies
- Types of data processing and analysis.
- Generate initial added value from data: Statistical analyses & visualizations.
- Overview of BI tools.
- Typical roles in data and AI projects (data analyst, data scientist, data engineer).
Learning environment
Once you have registered, you will find useful information, downloads and extra services relating to this training course in your online learning environment.
Your benefit
- You will have an overview of which data types and formats exist and why data is particularly important in the context of AI.
- They know the importance of good data quality and how to recognize poor quality.
- They know the advantages and disadvantages of the different data storage options.
- You will have an overview of the legal framework conditions that must be observed when storing and using data.
- You will be familiar with the most important types of data pre-processing and analysis and know what skills you need in your company to use data for artificial intelligence.
The training offers you:
- Practical exercises:
You apply what you have learned directly in practical exercises and thus consolidate your skills.
- Experienced lecturers:
The lecturers of the seminar are experts in the fields of data science and AI and have many years of practical experience.
- Networking opportunities:
You will have the opportunity to exchange ideas with other participants and expand your network in the areas of data literacy and AI.
Methods
Lecture to explain theory, discussion, practical case studies, independent completion of exercises, assistance from the trainer.
Recommended for
Digitization officers, innovation officers, project staff and interested specialists and managers who have little or no experience with data for artificial intelligence.
Further recommendations for "The right database for your AI applications"
Seminar evaluation for "The right database for your AI applications"







Start dates and details

Thursday, 31.07.2025
09:00 am - 12:30 pm
Thursday, 07.08.2025
09:00 am - 12:30 pm

Monday, 03.11.2025
09:00 am - 12:30 pm
Monday, 10.11.2025
09:00 am - 12:30 pm