Conferences and Seminars

During the seminar, you will learn, which steps are necessary to implement AI in production using concrete use cases as examples. The individual steps are accompanied by practical exercises in which you as a participant preprocess data sets, train ML-algorithms and evaluate the results of these models yourself using the Python programming language.

During the seminar, you will learn, which steps are necessary to implement AI in production using concrete use cases as examples. The individual steps are accompanied by practical exercises in which you as a participant preprocess data sets, train ML algorithms and evaluate the results of these models yourself using the Python programming language.

Within seven modules, the most relevant phases and principles for applying ML and AI in production are presented. In every step, a comprehensive methodological overview and hurdles to be overcome within an AI implementation are presented. The theoretical sessions are further accompanied by practical exercises through hands-on programming modules, in which the participants are implementing ML models.

In this seminar, benefits of AutoML systems are presented and when AutoML systems can be applied in production. Based on introductions into the topic ML and AI, its tools and methodologies, ML models are implemented manually. Then, AutoML tools are benchmarked with the manual implementation and influencing factors on the performance of AutoML tools are discussed. Finally a tool for selecting the right AutoML tool will be presented.