- Machine Learning Basics
- Hierarchical Clustering in R
- Time Series Analysis in R
- R programming basics
- Linear Regression in R
- Logistic Regression in R
- Decision Tree in R
- Random Forest in R
- Support Vector Machine in R

- Aspiring Data Scientists
- Software Engineers
- Web developers
- AIML enthusiasts

### Introduction to Machine Learning with R

#### Introduction

01:34##### Introduction

01:34

#### Lesson 01: Introduction to Machine Learning

07:07##### Introduction to Machine Learning

07:07

#### Lesson 02: Machine Learning Applications

04:58##### Machine Learning Applications

04:58

#### Lesson 03: R programming Introduction and Installation

10:34##### R programming Introduction and Installation

10:34

#### Lesson 04: Variables Data Types and Logical Operators in R

33:12##### Variables Data Types and Logical Operators in R

33:12

#### Lesson 05: Vectors and Lists in R

29:51##### Vectors and Lists in R

29:51

#### Lesson 06: Matrix and Data Frames in R

01:39:11##### Matrix and Data Frames in R

01:39:11

#### Lesson 07: Flow Control

23:38##### Flow Control

23:38

#### Lesson 08: Functions in R

01:19:56##### Functions in R

01:19:56

#### Lesson 09: Data Manipulation in R-dplyr and R-tidyr

32:44##### Data Manipulation in R-dplyr and R-tidyr

32:44

#### Lesson 10: Data Visualization in R

28:33##### Data Visualization in R

28:33

#### Lesson 11: Linear Regression in R

28:45##### Linear Regression in R

28:45

#### Lesson 12: Logistic Regression in R

18:17##### Logistic Regression in R

18:17

#### Lesson 13: Decision Tree in R

44:19##### Decision Tree in R

44:19

#### Lesson 14: Random Forest in R

25:27##### Random Forest in R

25:27

#### Lesson 15: Support Vector Machine in R

37:05##### Support Vector Machine in R

37:05

#### Lesson 16: Hierarchical Clustering in R

23:52##### Hierarchical Clustering in R

23:52

#### Lesson 17: Time Series Analysis in R

01:10:30##### Time Series Analysis in R

01:10:30

Share your certificate with prospective employers and your professional network on LinkedIn.

Expected machine learning market growth by 2022

Â

In the adoption of machine learning in organizations

About The Course

In this course, you will **learn Machine Learning with R for free**. You will work through practical examples to implement machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, SVM, and hierarchical clustering. Through interactive exercises, you'll apply these algorithms to real-world scenarios, gaining a practical understanding of their applications. Additionally, you will dive into R programming through guided exercises, learning how to write code and manipulate data for machine learning tasks. The course will also feature practi

### Why choose R for Machine Learning?

R stands out for its robust ecosystem, particularly in typical machine learning and data mining techniques. With powerful statistical analysis capabilities on massive datasets, R provides various options for exploring data, facilitates the use of probability distributions, and supports the application of diverse statistical tests.

### What are some challenges in Machine Learning with R?

Challenges in machine learning with R can include data cleaning and preprocessing complexities, limited scalability for large datasets, and the need for additional libraries for certain advanced machine learning models.

### Can R handle Deep Learning?

Yes, R can handle Deep Learning through interfaces like Keras. Keras for R allows data scientists to leverage deep learning models within an R environment, providing familiar syntax while harnessing the power of deep learning methods and architecture.

### Will I receive any certification upon completing this free Machine Learning with R course?

Yes, a completion certificate will be awarded upon successfully finishing the

**Machine Learning with R free course.**### How long will I have access to the course materials?

You will have access to the

**free Machine Learning with R course**materials for 90 days, allowing ample time for self-paced learning.### What is the course duration?

The

**Machine Learning with R free course**spans 10 hours of self-paced video lessons, providing comprehensive coverage of machine learning concepts with R.

- Disclaimer
- PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.