Live In-Person Event
Better, Stronger, Faster with Machine Learning: Equipping Scientists and Engineers to Transform Industry
Join us for an enlightening, in-person event in Bloomington, MN, and explore how advanced analytics and machine learning can accelerate innovation and drive meaningful results.
Date: Tuesday, Oct. 6
Time: 2-5 p.m.
Venue: Lake Normandale Office Park
Location: 8400 Normandale Lake Boulevard
Bloomington, MN 55437
Registration: Free, but registration is required.
Most organizations don't struggle because they lack AI. They struggle because they can't turn data into answers fast enough. Too much time is spent debating tools, evaluating technologies, and chasing the latest trends. Too little time is spent understanding what is driving performance, why processes behave the way they do, which decisions matter most, and how to improve outcomes with confidence.
In this seminar, we explore the practical ways scientists and engineers are using advanced analytics and machine learning to solve real-world problems. Discover how organizations are accelerating learning, uncovering critical insights faster, scaling expertise across teams, and making better decisions throughout research, development, and operations. Learn how to separate AI hype from practical value and explore where machine learning can help, where traditional analytical methods may be more effective, and how the two work together to drive meaningful results, because the goal isn't better AI — it's getting answers faster so you can get back to engineering.
Agenda
2:00-2:30 p.m.
Registration and networking
2:30-3:30 p.m.
From Data to Decisions: Better Modeling for Faster Learning and Better Outcomes
While AI continues to generate excitement, organizations achieve sustainable results by applying rigorous statistical thinking to understand processes, identify drivers of performance, and make more confident decisions. This session demonstrates how scientists and engineers use statistical modeling techniques in JMP and JMP Pro to transform data into actionable knowledge. Through real-world examples from manufacturing, R&D, and quality improvement initiatives, learn how modern analytical methods can uncover critical relationships, quantify uncertainty, and accelerate learning without requiring a team of data scientists.
Topics include:
- Building reliable predictive models to understand complex relationships and support data-driven decision making.
- Identifying the factors that matter most using modeling techniques to uncover key process drivers, interactions, and sources of variation.
- Turning analytical results into action by interpreting model insights, quantifying uncertainty, and communicating findings that drive better business and engineering decisions.
3:45-4:45 p.m.
Practical Machine Learning for Scientists and Engineers
Machine learning has become a powerful tool for uncovering patterns, predicting outcomes, and improving performance, but successful projects require a balance between advanced algorithms and domain expertise. This session explores how scientists and engineers can apply machine learning within JMP Pro to solve real industrial challenges while maintaining transparency and trust in their results.
Rather than focusing on hype, we discuss practical approaches that help organizations leverage machine learning to detect anomalies, classify outcomes, and uncover opportunities hidden within complex data.
Topics include:
- Applying the right analytical approach by understanding when machine learning provides advantages over traditional statistical methods.
- Developing accurate and robust predictive models using modern machine learning methods for prediction, classification, and pattern discovery in complex data.
- Building trustworthy insights from data through techniques that ensure reliable performance on new, unseen data.
4:45-5:00 p.m.