Description
Artificial intelligence (AI) is increasingly revolutionizing analytics and measurement technology in laboratories. From chemical analysis and biological tests to physical measurement technology and medical diagnostics: AI-supported processes accelerate data processing, increase precision and optimize workflows.
Modern algorithms recognize patterns in complex data sets, evaluate results in real time and provide a basis for decision-making that goes far beyond traditional analysis methods.
Laboratories generate huge amounts of data every day: from R&D projects, from development and approval studies or from routine measurements in quality control. These data sets often include extensive measurement and analysis data that is available in various formats and systems: from modern laboratory information management systems to historical data lakes. Often this data is not used, but only managed.
This seminar teaches how
- AI can be used specifically in various areas of analytics and measurement technology.
- you can exploit the full potential of your laboratory data with the help of artificial intelligence (AI).
- You can gain valuable insights from your data that not only improve laboratory processes, but also create added value for customers, and how you can use them to develop new business models.
This seminar is aimed at
- Laboratory managers and management functions in research, development and quality control who wish to acquire a basic understanding of the use of AI in the laboratory environment.
- Quality managers and QA officers who want to use the advantages of AI to optimize their laboratory and quality processes.
- IT, LIMS and data managers who are preparing to implement AI solutions in the laboratory.
After the seminar
- you will have become familiar with the basic concepts and decision criteria for the use of AI in various analytical methods and measurement technology.
- you will be able to assess which laboratory processes are best suited for the implementation of AI technologies and which are not.
- know specific use cases in which AI is used to improve measurement data evaluation and automate reporting.
- you know how data can be analyzed in order to optimize existing processes and products and thus significantly increase efficiency and quality.
You can find the complete program here.
