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

Motivation

• High-quality data forms the basis of all data-driven solutions, such as predictive maintenance or predictive quality
• Companies know about the fact that data quality is first and foremost when it comes to data analytics and artificial intelligence

However, companies often lack

• experience how to ensure and obtain high-quality data,
  
• the know-how regarding an efficient and structured use of data
• Which tools to be used to increase data quality

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