Welcome to the 2-hour long project-based course on Principal Component Analysis with NumPy and Python. In this project, you will delve into the depths of machine learning, implementing all the machinery of various learning algorithms without using popular machine learning libraries such as scikit-learn and statsmodels. By the end of this course, you will have a solid understanding of implementing and applying PCA from scratch using NumPy in Python, conducting basic exploratory data analysis, and creating simple data visualizations with Seaborn and Matplotlib.
The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory. This course runs on Coursera's hands-on project platform called Rhyme, providing instant access to pre-configured cloud desktops containing all the necessary software and data. Everything is pre-installed, allowing you to focus solely on learning.
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