AI Manager: Classification of AI Models

Course overview

Artificial intelligence is fundamentally changing the economy, science, and society. To successfully implement AI systems, it is essential to have not only an understanding of the technological foundations but also knowledge about data, methods, application areas, as well as the planning and evaluation of AI projects. In this course, you will learn the key concepts of artificial intelligence and develop an understanding of the practical application of AI - from the idea to the testing of an AI system. Content: Fundamentals, history, and development of artificial intelligence Distinction of AI from related technologies such as machine learning, big data, and automation Strengths, limitations, and technological and ethical challenges of AI systems Types of data, data quality, and the importance of training, validation, and test data Applications of AI in business, research, and various industries Assessment of potentials, opportunities, and risks of AI applications Development and planning of AI concepts as well as selection of suitable models and algorithms Integration of AI solutions into existing business processes Testing, validation, and evaluation of AI models using appropriate methods and metrics Practical development and implementation of AI pilot projects Perspectives: The acquired knowledge provides a foundation for activities in the field of artificial intelligence, data science, business analytics, digitalization, innovation management, project management, process optimization, as well as in specialist and consulting functions of companies, research institutions, and public organizations that develop or use AI technologies. If you have any questions about this or about combination options, please feel free to contact our advisory service.

Upcoming dates

• 2026-10-20T22:00:00.000Z · 2026-11-02T23:00:00.000Z · Aachen · Blended Learning
• 2026-10-20T22:00:00.000Z · 2026-11-02T23:00:00.000Z · Virtuelles Klassenzimmer
• 2026-10-20T22:00:00.000Z · 2026-11-02T23:00:00.000Z · Altenburg, Thüringen · Blended Learning
• 2026-10-20T22:00:00.000Z · 2026-11-02T23:00:00.000Z · Amberg, Oberpfalz · Blended Learning
• 2026-10-20T22:00:00.000Z · 2026-11-02T23:00:00.000Z · Ansbach, Mittelfranken · Blended Learning