Course Curriculum

    1. Why Take This Course?

      FREE PREVIEW

    2. Conventions and Orientation

    3. Download Materials

    4. New to JMP

    1. Factorial versus Mixture Designs

    2. Systems Thinking

    1. Mixture Spaces, Components and Blending

    2. Mixture Design Basics Quiz

    1. Modeling Mixture Experiments

    2. Modeling Mixture Experiments Quiz

    3. Case Study: Etch Rate

    4. Case Study: Etch Rate Quiz

    1. Types of Mixture Designs

    2. Types of Mixture Designs Quiz

    3. Case Study: Yarn

    4. Case Study: Yarn Quiz

    5. Case Study: Etch Rate (SFD)

    6. Case Study Etch Rate (SFD) Quiz

    1. Modern Machine Learning Example Part 1

    2. Machine Learning and Ensemble Modeling Part 2

    3. Machine Learning and Ensemble Modeling Quiz

About this course

  • $995.00
  • 18 hours of video content
  • Corporate Discounts Available

Additional Details

Applications pertain to a wide variety of industrial sciences. Examples include:

  • Pharmaceutical & Bio-engineering

    Conducting media or buffer optimization experiments for increased protein yields from bacteria or mammalian cells.

  • Semiconductor

    Semi-conductors, modeling yield on wafers, identifying yield loss mechanics, and investigating new wafer substrates.

  • Materials

    Improving asphalt mixtures for critical process attributes. Optimizing critical characteristics in metallurgy.

Instructors

Senior Data Scientist, Predictum Inc. Philip Ramsey

Phil is a Senior Data Scientist and Statistical Consultant at Predictum. He provides consulting services in data science, statistics, and machine learning for integrated analytical systems, custom projects, and training. He specializes in modern experimental design and analysis strategies and the use of statistics, data science, and machine learning in engineering and science. In addition, Phil is a Professor in the Department of Mathematics and Statistics at the University of New Hampshire (UNH) where he teaches courses at the undergraduate and graduate levels in design of experiments, machine learning, and statistical methods for quality improvement. He has held the following relevant industrial positions: Senior Engineer for Materials and Processes Development, McDonnell Douglas, St. Louis, MO; Staff Scientist/Statistician, Alcoa Technical Center, Pittsburgh, PA; and Statistician/Senior Engineer, Rohm & Haas Electronic Materials (now Dow), Marlboro, MA. Phil holds a Ph.D. in statistics from Virginia Polytechnic Institute and State University.

Senior Data Scientist, Predictum Inc. Marie Gaudard

Marie is a Senior Data Scientist at Predictum. She specializes in predictive modeling, design of experiments, statistics, and machine learning. She has extensive experience in consulting and statistical training in a wide variety of industries. Marie is Professor Emerita of Statistics at the University of New Hampshire (UNH), where she has worked extensively with students and companies on the practical application of statistics. She is also a co-author of two books, one of which is about the use of JMP software and statistical methods to improve quality and the other is about the partial least squares technique. She was also a statistical writer for several years as a member of the JMP documentation team at SAS Institute. Marie holds a Ph.D. in Statistics from the University of Massachusetts at Amherst.