Factor Analysis and PCA are key techniques for dimensionality reduction, and latent factor identification. In this course, Understanding and Applying Factor Analysis and PCA, you'll learn how to understand and apply factor analysis and PCA. First, you'll explore how to cut through the clutter with factor analysis. Next, you'll discover how to carry out factor analysis using PCA, a powerful ML-based approach. Then, you'll learn how to perform eigenvalue decomposition, a cookie-cutter linear algebra procedure. Finally, you'll learn how to implement PCA to explain Google's stock returns in Excel and VBA, R, and Python. By the end of this course, you'll have a strong applied knowledge of factor analysis and PCA that will help you solve complex business problems.