 Questions? Call 0345 053 7673 or Email us HERE. ### Machine Learning : Factor Analysis Online Course

[ TTMLFA ]

£27.00 £48.00

Seen this product cheaper elsewhere?

## Course Description

This ’Factor Analysis’ online training course will help you understand Factor Analysis and its link to linear regression. See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how it relates to Machine Learning.

Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect. In this course, you will follow along with expert instructors to learn about topics such as Mean & Variance, Eigen Vectors, Covariance Matrices, and so much more!

Course Highlights:
• Understand & Analyze Principal Components
• Use Principal Components for dimensionality reduction and exploratory factor analysis
• Apply PCA to explain the returns of a technology stock like Apple®
• Build Regression Models with Principal Components in Excel, R, & Python

Course Requirements:

• No statistics background required. Everything is built up from basic math.
• The models are implemented in Excel, R, & Python. Install these environments to follow along with the demos.

Target Audience:

• Data analysts who want to move from summarizing data to explaining and prediction
• Folks aspiring to be data scientists
• Any business professionals who want to apply Factor Analysis and Linear Regression to solve relevant problems
Length: 1 hr 45 min

## Course Outline

Chapter 01: Introduction

• Lesson 01: You, This Course, & Us!

Chapter 02: Factor Analysis & PCA

• Lesson 01: Factor Analysis & the Link to Regression
• Lesson 02: Factor Analysis & PCA

Chapter 03: Basic Statistics Required for PCA

• Lesson 01: Mean & Variance
• Lesson 02: Covariance & Covariance Matrices
• Lesson 03: Covariance vs Correlation

Chapter 04: Diving into Principal Components Analysis

• Lesson 01: The Intuition Behind Principal Components
• Lesson 02: Finding Principal Components
• Lesson 03: Understanding the Results of PCA – Eigen Values
• Lesson 04: Using Eigen Vectors to find Principal Components
• Lesson 05: When not to use PCA

Chapter 05: PCA in Excel

• Lesson 01: Setting up the data
• Lesson 02: Computing Correlation & Covariance Matrices
• Lesson 03: PCA using Excel & VBA
• Lesson 04: PCA & Regression

Chapter 06: PCA in R

• Lesson 01: Setting up the data
• Lesson 02: PCA and Regression using Eigen Decomposition
• Lesson 03: PCA in R using packages

Chapter 07: PCA in Python

• Lesson 01: PCA & Regression in Python

PACKAGE INCLUDES:

Length of Subscription: 12 Months Online On-Demand Access
Running Time: 1 hrs 45 min
Platform: Windows & MAC OS
Project Files: Included

Learn anytime, anywhere, at home or on the go.