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AI – Factor Analysis with Excel, R and Python 2017

£239.00 £21.95

Our ’Factor Analysis’ e-Learning course will help you to 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. Supplemental Materials included!

SKU: EC4Y0252 Categories: , Tag:

Our ’Factor Analysis’ e-Learning course will help you to 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. Supplemental Materials included!

What is Factor Analysis?

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 much much more!

What’s Included?

Wiki_tick  Unlimited access for 12 months
Wiki_tick  Access anywhere, any time
Wiki_tick  Fast effective training, written and designed by industry experts
Wiki_tick  Track your progress with our Learning Management System
Wiki_tick  Unlimited support
Wiki_tick  Save money, time and travel costs
Wiki_tick  Learn at your own pace and leisure
Wiki_tick  Easier to retain knowledge and revise topics than traditional methods
Wiki_tick  Exam preparation quizzes, tests and mock exams to ensure that you are 100% ready

£239.00 £21.95Add to cart

Modules

Course Duration: 1.75 Hours

Chapter 01: Introduction

You, This Course, & Us!

Chapter 02: Factor Analysis & PCA

Factor Analysis & the Link to Regression
Factor Analysis & PCA

Chapter 03: Basic Statistics Required for PCA

Mean & Variance
Covariance & Covariance Matrices
Covariance vs Correlation

Chapter 04: Diving into Principal Components Analysis

The Intuition Behind Principal Components
Finding Principal Components
Understanding the Results of PCA – Eigen Values
Using Eigen Vectors to find Principal Components
When not to use PCA

Chapter 05: PCA in Excel

Setting up the data
Computing Correlation & Covariance Matrices
PCA using Excel & VBA
PCA & Regression

Chapter 06: PCA in R

Setting up the data
PCA and Regression using Eigen Decomposition
PCA in R using packages

Chapter 07: PCA in Python

PCA & Regression in Python

System Requirements

Minimum specifications for the computer are:

Windows:

Microsoft Windows XP, or later
Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)

MAC/iOS:

OSX/iOS 6 or later
Modern and up to date Browser (Firefox, Chrome, Safari)

All systems:

Internet bandwidth of 1Mb or faster
Flash player or a browser with HTML5 video capabilities (We recommend Google Chrome)

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