Principal Component Analysis (PCA) and Factor Analysis - Udemy

The course explains one of the important aspect of machine learning - Principal component analysis and factor analysis in a very easy to understand manner. It explains theory as well as demonstrates how to use SAS and R for the purpose. 

The course provides entire course content available to download in PDF format, data set and code files. The detail course content is as follows.

• Intuitive Understanding of PCA 2D Case
• what is the variance in the data in different dimensions?
• what is principal component?
• Formal definition of PCs
• Understand the formal definition of PCA

• Properties of Principal Components
• Understanding principal component analysis (PCA) definition using a 3D image

• Properties of Principal Components
• Summarize PCA concepts
• Understand why first eigen value is bigger than second, second is bigger than third and so on
• Data Treatment for conducting PCA
• How to treat ordinal variables?
• How to treat numeric variables?

• Conduct PCA using SAS: Understand
• Correlation Matrix
• Eigen value table
• Scree plot
• How many pricipal components one should keep?
• How is principal components getting derived?

• Conduct PCA using R

• Introduction to Factor Analysis
• Introduction to factor analysis
• Factor analysis vs PCA side by side

• Factor Analysis Using R
• Factor Analysis Using SAS
• Theory for using PCA for Variable Selection
• Demo of using PCA for Variable Selection