Introduction to Machine Learning key methods in JMP – 16th May 2024 @ 14:00 (GMT+1)

Pre-Requisites:

• Understanding of basic statistics (e.g. Descriptive statistics, sampling variability, hypothesis testing) and statistical terminology such as Standard Deviation (SD), Variance, Standard Error (SE), Confidence Intervals (CI) and p-values
• If you do not have these skills or need a refresher webinar, please contact us before booking this course so we can provide you with some help.

Course Content:

This covers a broad introduction to some of the most popular machine learning methods that are applicable to R&D companies with reasonably large data sets (rather than the likes of Zeta-bytes collected per second in some industries). An introduction to the stats behind the methods will be given, limiting the use of algebra and technical details as much as possible and instead focusing on the application and set up in JMP, with interpretation of the resulting outputs. Real data examples will be used to demonstrate the pro’s and con’s of each method. The topics covered in this half-day session are as follows:

1. Intro and Background
2. Unsupervised ML methods: Principal Components Analysis (PCA) and Partial Least Squares Regression (PLS-R)
3. Supervised ML methods: Decision Trees and Random Forests, Neural Networks
4. Summary and Discussion of Issues

The course will include live lectures online as well as workshops for the participants to complete during the session using JMP and the data sets provided, to ensure that the material covered can be repeated on the participants own data after the course with these workshops as guidance notes and templates for the set-up, analysis and results interpretation process.

About the Trainer:

Gemma has worked as a statistician, project manager, trainer and business consultant for over 25 years across a wide variety of projects within large and small multidisciplinary teams. Gemma has an MSc in Medical Statistics, was a statistician and a global project manager at Pfizer, then Takeda Global R&D, before joining Qi in 2012. Gemma’s business background and excellent statistical and communication skills are invaluable to our clients wanting to maximise information for competitive advantage from their data. Gemma now owns Qi and is the Director of Qi Statistics, but her ultimate goal is to be able to explain anything statistical to anyone, whatever their background or knowledge level.