Level: Beginner
Aiming to speed up research and development, Nippon Shokubai has been training data science talent among its experimental researchers since 2020. JMP, which is easy to use even for statistical novices, has been adopted as the standard tool, and a comprehensive approach that includes not only methodological education but also practical support has resulted in a variety of use cases.
However, while there were success stories, there were also voices saying, "It didn't work as planned," and "I don't know what I'm doing wrong." We thought it was important to experience a series of initiatives starting from designing the problem, rather than just practicing with ready-made data such as sample data.
The Flying Ball Simulator is an excellent JMP add-in that allows users to practically learn the PDCA cycle of Plan, Execute, Analyze, and Improve. Its unique feature is that designers can freely set the level design, and this time we developed experience content for the Design of Experiments method, assuming situations that materials development researchers are likely to encounter.
In this presentation, we will introduce our human resource development efforts and the educational content we developed using a flying ball simulator. We will also introduce the "JMP Trainers Study Group" hosted by SAS, which was used to create the educational content.
He specializes in mesosimulation of polymers and started working in data science in 2018. Through data analysis, he supports data-driven decision-making in materials research and production. Since 2020, he has been involved in educating and promoting in-house data scientists, and has conducted courses using JMP (material formulation design, experimental planning, production data analysis, etc.) and in-house LTs.
Recently, he has been participating in JMP Trainers study sessions hosted by SAS, and is focusing on developing experiential educational content.
*The video will be available until Sunday, December 18th.
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