Summer School | Artificial Intelligence in Production

Get to know tools, methods, and approaches of AI for image processing in quality inspection. Different use cases will be presented, and benefits and limits will be discussed. During a practical hands-on session, students will learn how to train an AI algorithm. Additionally, several applications are shown, which allow to comprehend possible industrial scenarios.

Receive an overview of the fundamental concepts and techniques involved in training and deploying language models. Students gain hands-on experience with cloud-based tools to understand the practical aspects of building and running language models at scale. The course covers topics of natural language processing, training of language models, and their deployment into a cloud computing infrastructure.

Students are introduced to artificial intelligence techniques for optimizing maintenance operations in the industry. They learn about the principles of predictive maintenance, including data collection, feature engineering, and model development. The course covers algorithms of deep learning and explores their application to predict and prevent equipment failures, optimize maintenance schedules, and reduce downtime. Practical exercises and case studies provide students with hands-on experience in implementing predictive maintenance solutions using real-world datasets.

Acquire skills in the field of automation and robotics with a focus on industrial and collaborative robots. Emphasis will be put on the topic robot-human interaction and its different frameworks in the market according to restrains and levels of interaction. Additionally, automation examples are shown, which allow to comprehend possible industrial applications.

In this module, the instructors will introduce the fundamentals and basic methods of artificial neural networks and how they are applied in deep learning. The participants will learn how to train these models and generate a working agent.