Machine Learning in Excel

Name: Machine Learning in Excel Course
Price: 36 USD

with Ivan Kitov

4.9/5

(547)

Master the core concepts of popular ML algorithms with hands-on projects in Excel’s beginner-friendly environment

7 hours of content 7665 students

$99.00

Lifetime access

Buy now

14-Day Money-Back Guarantee

What you get:

7 hours of content
86 Interactive exercises
63 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

Machine Learning in Excel

A course by Ivan Kitov

$99.00

Lifetime access

Buy now

14-Day Money-Back Guarantee

What you get:

7 hours of content
86 Interactive exercises
63 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now

14-Day Money-Back Guarantee

What you get:

7 hours of content
86 Interactive exercises
63 Downloadable resources
World-class instructor
Closed captions
Q&A support
Future course updates
Course exam
Certificate of achievement

What You Learn

Acquire machine learning skills that bridge theoretical knowledge and practical application
Gain insight into the strength and limitations of various machine learning models
Leverage Excel’s beginner-friendly environment for hands-on machine learning modeling
Understand fundamental machine learning theory that will help you achieve outstanding real-world results
Combine Azure and Microsoft Excel to run ML experiments in the cloud
Improve your career prospects with in-demand machine learning skills, essential for your success in an AI-driven world

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

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.

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1.1 Course Introduction

5 min

1.2 What Is Machine Learning?

8 min

1.3 Types of Machine Learning

5 min

2.1 Linear Regression: Introduction

2 min

2.3 Linear Regression

5 min

2.5 Linear Regression Model (Graphical Representation)

3 min

Interactive Exercises
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Curriculum

1. Introduction

3 Lessons 18 Min

In this introductory section, we will discuss why you need to learn advanced statistics, what sets this discipline apart from machine learning, and how you can get the most out of the Machine Learning in Excel course.

Course Introduction
5 min
What Is Machine Learning?
8 min
Types of Machine Learning
5 min
2. Simple Linear Regression

10 Lessons 49 Min

Join us to create your first simple regression in Excel and get familiar with a very important statistical concept – the Ordinary least squares framework. You will learn about OLS assumptions, how to interpret regression results, as well as how to decompose variability.

Linear Regression: Introduction
2 min
Linear Regression
5 min
Linear Regression Model (Graphical Representation)
3 min
Formatting Excel Spreadsheets
1 min
First Regression in Excel
7 min
What Is OLS?
3 min
Interpreting Regression Tables (Part 1)
9 min
Decomposition of Variability
4 min
Interpreting Regression Tables (Part 2)
9 min
Interpreting Regression Tables (Part 3)
6 min
3. Multiple Linear Regression

13 Lessons 49 Min

In section 3 you will discover multiple linear regression. We will expand on the simple linear regression techniques we covered in the previous section and discuss some practical considerations such as working with dummy variables and how to make predictions with more than one independent variable using Excel.

Multiple Regression Analysis
3 min
Multiple Linear Regression (Example)
7 min
Multiple Linear Regression (Results)
7 min
OLS Assumptions
3 min
OLS Assumptions: Linearity
2 min
OLS Assumptions: No Endogeneity
4 min
OLS Assumptions: Normality and Homoscedasticity
5 min
OSL Assumptions: No Autocorrelation
4 min
OLS Assumptions: No Multicollinearity
4 min
Dummy Variables
5 min
Dummy Variables - Exercise Read now
1 min
Making Predictions Using Linear Regression
3 min
Making Predictions Using Linear Regression -Exercise Read now
1 min
4. Linear Regression Practical Example

6 Lessons 42 Min

An all-in-one use case that tests your understanding of each of the concepts you mastered so far. We will focus on a property price dataset and create a linear regression model to predict house prices.

Practical Example (part 1)
11 min
Practical Example (part 2)
6 min
Practical Example (part 3)
10 min
A note on multicollinearity Read now
1 min
Feature Scaling
3 min
Practical Example (part 4)
11 min
5. Logistic Regression

12 Lessons 70 Min

This section of the course covers logistic regression. You will grasp the difference between logistic and logit regression, the concepts of ROC curve, underfitting and overfitting, and how to interpret results from a logistic regression. Of course, you will see a practical example of how to perform this type of regression in Excel and calculate the accuracy of your model.

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

4 Lessons 15 Min

Cluster analysis is the most intuitive and important example of unsupervised learning. However, to be able to understand cluster analysis, you must first become familiar with the mathematics behind it. Here we will explore the fundamentals of cluster analysis and have a look at the differences between clustering and classification.

Cluster Analysis (Definition)
4 min
Cluster Analysis (Application)
5 min
Clustering vs Classification
3 min
Cluster Analysis (Math Prerequisites)
3 min
7. K-means Clustering

11 Lessons 58 Min

Master K-means clustering in Excel by learning how to choose the number of clusters in your analysis and determine when to standardize or not standardize your data. At the end of this section, we will go through a complete practical example that includes marketing segmentation with cluster analysis.

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

6 Lessons 28 Min

With the use of visual examples this section of the course introduces you to the concept of decision trees. We will cover the advantages and disadvantages of this method and explore its inner workings – how is the tree constructed and what metrics are used in its construction. This will be followed up by a practical example showcasing how to create decision trees in Excel.

Decision Trees
3 min
Entropy (Loss function)
5 min
Information Gain
5 min
Decision Trees in Excel (Part 1)
7 min
Decision Trees in Excel (part 2)
4 min
Decision trees (Prediction)
4 min
9. Machine Learning in the Cloud

8 Lessons 30 Min

In the final section of the course, we will combine Azure and Microsoft Excel to run ML experiments in the cloud. In our case, we’ll create a predictive analytics model in Azure Machine Learning Studio.

Machine Learning in the Cloud
4 min
Setting up Azure Machine Learning Studio (AMLS)
3 min
First Experiment in AMLS (Part 1)
8 min
First Experiment in AMLS (Part 2)
5 min
Machine Learning in the Cloud (Assignment) Read now
1 min
Publishing a Web Service
5 min
Azure Assignment
3 min
The Future of Machine Learning Read now
1 min

Topics

Regression AnalysisMachine LearningK-Means ClusteringAzure Machine Learning StudioData AnalysisTheoryExcelLogistic RegressionDecision TreesMachine and Deep LearningSpreadsheets

Tools & Technologies

Course Requirements

Highly recommended to take the Intro to Excel, Statistics, Math, and Probability courses first
You will need Microsoft Office

Who Should Take This Course?

Level of difficulty: Intermediate

Aspiring data scientists and ML engineers
ML enthusiasts who want to learn in a beginner-friendly environment

Exams and Certification

A 365 Financial Analyst Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Meet Your Instructor

Ivan Kitov

COO at

8 Courses

2968 Reviews

34996 Students

Ivan is the COO of 365 Data Science and a CFA charterholder with over 12 years of professional experience in the financial sector. He earned his Master’s degree in Financial Economics from the Erasmus University of Rotterdam, the Netherlands in 2010 and has been fascinated by the world of artificial intelligence and machine learning ever since. Seeing how data science truly redefined the finance industry over the last decade, Ivan knew that he couldn’t stay on the sidelines. In 2019, he published his first online course on corporate finance, combining his expertise with his love of teaching. His goal is to establish 365 Data Science as the best learning platform for aspiring data professionals in the world.