Machine Learning in Excel

Introducing you to the essentials of machine learning in Excel with beginner-friendly, hands-on projects. You will learn how to use linear and logistic regression, k-means clustering, decision trees, and Azure ML Studio.

with Ivan Kitov

Course Overview

This course focuses on predictive modeling and enters multidimensional spaces that require an understanding of mathematical methods, transformations, and distributions. We will introduce you to all these concepts, gradually blending them into complex means of analysis such as k-means clustering and decision trees, while helping you hone your Excel skills.

70 High Quality Lessons

22 Practical Tasks

6 Hours of Video

Certificate of Achievement

Skills you will gain

data analysisexcelmachine learningtheory

What You'll Learn

This course will help you master predictive modeling with multiple different approaches such as linear regression, logistic regression, cluster analysis, and decision trees in Excel. By the end of the course, you’ll understand the intuition behind machine learning algorithms and will be able to apply your knowledge in practice.

Perform linear regression

Grasp logistic regression

Implement K-means clustering

Approach decision trees

Explore the future of machine learning in the cloud

Upgrade your Excel skills

Curriculum

Introduction Free

3 Lesson 18 Min

Course Introduction Free What Is Machine Learning? Free Types of Machine Learning Free
Simple Linear Regression

10 Lesson 49 Min

Linear Regression: Introduction Free Linear Regression Free Linear Regression Model (Graphical Representation) Free Formatting Excel Spreadsheets Free First Regression in Excel Free What Is OLS? Free Interpreting Regression Tables (Part 1) Free Decomposition of Variability Free Interpreting Regression Tables (Part 2) Interpreting Regression Tables (Part 3)
Multiple Linear Regression

11 Lesson 47 Min

Multiple Regression Analysis Multiple Linear Regression (Example) Mutiple Linear Regression (Results) OLS Assumptions OLS Assumptions: Linearity OLS Assumptions: No Endogeneity OLS Assumptions: Normality and Homoscedasticity OSL Assumptions: No Autocorrelation OLS Assumptions: No Multicollinearity Dummy Variables Making Predictions Using Linear Regression
Linear Regression Practical Example

6 Lesson 41 Min

Practical Example (part 1) Practical Example (part 2) Practical Example (part 3) A note on multicollinearity Feature Scaling Practical Example (part 4)
Logistic Regression

12 Lesson 70 Min

Introduction to Logistic Regression From Linear to Logistic Regression Logistic vs. Logit Function Applying Logistic Regression in Excel Interpreting Regression Coefficients Logistic Regression with Xreal Understanding the Logistic Regression Summary (part 1) Understanding the Logistic Regression Summary (Part 2) ROC Curve Binary Predictors for Logistic Regressions Underfitting and Overfitting Testing the Logistic Model
Cluster Analysis

4 Lesson 15 Min

Cluster Analysis (Definition) Cluster Analysis (Application) Clustering vs Classification Cluster Analysis (Math Prerequisites)
K-means Clustering

11 Lesson 58 Min

K-means Clustering K-means Clustering in Excel K-means Clustering with Xreal Choosing the Number of Clusters Clustering Categorical Data Standardization Clustering and Regression Clustering (Pros and Cons) Types of Clustering Market Segmentation (Part 1) Market Segmentation (Part 2)
Decision Trees

6 Lesson 28 Min

Decision Trees Entropy (Loss function) Information Gain Decision Trees in Excel (Part 1) Decision Trees in Excel (part 2) Decision trees (Prediction)
Machine Learning in the Cloud

7 Lesson 28 Min

Machine Learning in the Cloud Setting up Azure Machine Learning Studio (AMLS) First Experiment in AMLS (Part 1) First Experiment in AMLS (Part 2) Publishing a Web Service Azure Assignment The Future of Machine Learning

“In the last 10 years machine learning has redefined industries such as finance, banking, and investments. This course will help you learn the advanced statistical techniques employed by successful data analysts. You will grasp the intuition behind regression analysis, clustering, and decision trees without having to code at all! Excel is the perfect environment to understand and apply different machine learning techniques in an easy-to-follow way.”

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