Principal Component Analysis Courses and Certifications

StatQuest with Josh Starmer

Principal Component Analysis - PCA, Step-by-Step

Step-by-step guide to Principal Component Analysis (PCA), explaining its importance in data analysis and machine learning. Covers 2D and 3D data examples, PC calculation, and interpretation of results.

• YouTube
• 22 minutes
• On-Demand
• Free Video

StatQuest with Josh Starmer

Principal Component Analysis - PCA Clearly Explained - 2015

Clear explanation of Principal Component Analysis, covering dimensions, variance, loading scores, and key concepts for interpreting PCA plots in RNA-seq data analysis.

• YouTube
• 20 minutes
• On-Demand
• Free Video

The Julia Programming Language

Principal Component Analysis - Lecture 8

Explore Principal Component Analysis: from matrix rank to SVD. Learn to measure data cloud size, understand correlated data, and navigate high-dimensional spaces using statistical techniques.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Julia Silge

Principal Component Analysis for Hip Hop Songs With Tidymodels

Implement PCA using recipes to analyze the best hip hop songs of all time, exploring Spotify data and visualizing results with tidymodels.

• YouTube
• 1 hour
• On-Demand
• Free Video

Tom Rocks Maths

How to Find Patterns in Data - Principal Component Analysis (PCA)

Dive into Principal Component Analysis (PCA) with Oxford mathematician Dr. Tom Crawford, exploring how to identify patterns in complex datasets through eigenvectors, covariance matrices, and variance maximization.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Principal Component Analysis in Finance - Lecture 9

Discover how Principal Component Analysis transforms bond market modeling by identifying key yield curve factors for effective portfolio construction and risk management.

• YouTube
• 1 hour 23 minutes
• On-Demand
• Free Video

UofU Data Science

Principal Component Analysis - Dimensionality Reduction and SVD - L15

Master dimensionality reduction through dot-products, orthogonal projections, SVD, and Principal Component Analysis techniques for optimal data representation.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

DigitalSreeni

Principal Component Analysis (PCA) - Mastering Dimensionality Reduction and Visualization

Master PCA for dimensionality reduction with complete Python implementation, from mathematical foundations to 3D visualization using breast cancer classification case study.

• YouTube
• 41 minutes
• On-Demand
• Free Video

UofU Data Science

Principal Component Analysis and Singular Value Decomposition - Spring 2023

Master dimensionality reduction techniques through PCA and SVD, exploring multicollinearity, vector basis, and practical applications with hands-on demonstrations for effective data analysis.

• YouTube
• 1 hour 23 minutes
• On-Demand
• Free Video

UofU Data Science

Dimensionality Reduction: Principal Component Analysis and Multidimensional Scaling - Lecture 21

Master dimensionality reduction techniques through Principal Component Analysis (PCA) and Multidimensional Scaling (MDS), exploring their applications in data analysis and visualization.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Principal Component Analysis - Tutorial

Discover how to reduce data dimensionality and identify key patterns using Principal Component Analysis techniques in this concise tutorial.

• YouTube
• 12 minutes
• On-Demand
• Free Video

UofU Data Science

Data Mining Lecture 17 - Principal Component Analysis

Explore Principal Component Analysis (PCA) through projections, basis vectors, SVD, and eigendecompositions in this comprehensive data mining lecture.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Navigating Data Simplification with PCA

Master dimensionality reduction techniques using Principal Component Analysis (PCA) with Python's Scikit-learn, from basic concepts to practical implementation in machine learning projects.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Navigating Data Simplification with PCA

Master dimensionality reduction techniques using Principal Component Analysis in R, from understanding eigenvectors to implementing PCA for feature extraction and classification tasks.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Coursera

Principal Component Analysis with NumPy

298 ratings at Coursera

Implement Principal Component Analysis from scratch using NumPy, conduct exploratory data analysis, and create visualizations with Seaborn and Matplotlib in Python.

• Coursera
• 1 hour 35 minutes
• On-Demand
• Paid Course