Principal Component Analysis MasterClass - US edition

Learn everything you need to use the most common multivariate analysis method, principal component analysis (PCA).

14-15 November, 2024, Virtual
Time Zone: Eastern Standard Time (EST) - UTC - 05:00

Overview

Learn everything you need to use the most common multivariate analysis method, principal component analysis (PCA). With PCA you can easily visualize, understand and interpret highly complicated data sets without any need for programming or scripting. The teacher has +30 experience with teaching multivariate analysis to a chemical audience and is one the researchers with the highest impact within chemometrics - the field of applying machine learning and related methods in the chemical sciences. By attending this event, you will be able to critically perform PCA on your own data and without any need for programming or mathematical skills. You will see how you use PCA to identify outliers such as when detecting a process out of control or an adulterated sample. You will learn to identify which variables are causing which effects that you observe and you will be able to classify whether a sample belongs to one class of samples or another. And a lot of other things. Basically, you will learn to overview, visualize and understand multivariate data to the fullest.

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RECOMMENDATION
Who should attend?

R&D chemists (research and development)
R&D manager/engineer/analyst (in chemistry)
Metabolomics researcher/scientist/specialist
People working with proteomics, genomics, forensics, untargeted chemical profiling (GC MS, LS-MS, NMR)