Machine Learning (ML) and Artificial Intelligence (AI) in Production

Motivation

• AI offers the potential to increase product quality and process efficiency, while decreasing scrap rates and machine downtimes.
• Success stories of AI and ML in production are already known.

However, companies often lack

• the methodological knowledge to carry out AI-projects
• the know-how which tools to be used for AIimplementations
• experience in dealing with possible problems during implementation

Description

• In order to make full use of the potential of your data, this seminar teaches essential methods of data preparation.
• Based on concrete production success stories, data is prepared to gain knowledge of how to achieve high data quality.
• Thus, the necessary steps to achieve high data quality consisting of integrating, handling missing data and outliers, scaling features, encoding data, reducing dimensions and sampling data are discussed and implemented.

Goals

Enable you as a company to…

• enhance your data quality
• better use your data
• preprocess your data efficiently and structured
• increase the performance of your data analysis