Live-Veranstaltung vor Ort

Beyond the AI Hype: Practical Machine Learning for Scientists and Engineers

Jenseits des KI-Hypes: Machine Learning in der Praxis für Wissenschaft und Technik

12. November, 15:00-17:30, Spittelmarkt, Berlin

Artificial intelligence may dominate the headlines, but scientists and engineers face a different challenge: applying machine learning to solve real-world industrial problems in process industries such as biotech, semiconductor, pharmaceuticals and chemicals.

In this seminar, discover how machine learning and advanced analytics can help you uncover patterns in complex data, build more accurate predictive models, and make better decisions throughout research, development, and manufacturing. Through practical examples from R&D, manufacturing, and process improvement, we explore how these methods complement traditional statistical approaches and where they deliver the greatest value.

Whether you're taking your first steps into machine learning or looking to expand your analytical toolkit, you'll leave with a better understanding of today's methods, their practical applications, and how they can help you solve complex scientific and engineering challenges.

Join us for an afternoon of learning, discussion, and networking with fellow scientists and engineers.

Kurz zusammengefasst: Erfahren Sie anhand praxisnaher Beispiele, wie Machine Learning und moderne Analysemethoden in Forschung, Entwicklung und Produktion eingesetzt werden können – von der Erkennung komplexer Datenmuster bis hin zu präziseren Vorhersagemodellen und besseren Entscheidungen.

Agenda:

Time Topic Presenter
15:00 Registration & networking
15:20 Welcome and Introduction

Marcel Brüske, JMP

Angelina Moncelli, JMP

15:30

Machine Learning for Scientists and Engineers

  • What machine learning means for engineers and scientists
  • When to use ML vs traditional analysis methods
  • Building and interpreting predictive models in JMP Pro

Christian Zollner, JMP

Astrid Ruck, JMP

16:15 Coffee Break
16:30

Advanced Analytics and Optimization with JMP Pro

This session explores practical approaches to solving complex industrial challenges, including Bayesian optimization for efficient experimentation, complemented by one of the following advanced topics:

  • Functional Data Explorer: Curve modeling and golden curve optimization.
  • Design Space Profiler: Statistical tolerancing and enhanced limit and margin testing

Christian Zollner, JMP

Astrid Ruck, JMP

17:15 Q&A and closing

Marcel Brüske, JMP

Angelina Moncelli, JMP

17:30 Networking and refreshments
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