- 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

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Expected machine learning market growth by 2022

In the adoption of machine learning in organizations

### What are the prerequisites to get started with Machine Learning with R?

There are no prerequisites to learn Machine Learning with R. However, it is recommended that learners have a basic understanding of mathematics, statistics and programming.

### How do beginners get started with the Machine Learning with R free course?

Beginners who want to learn Machine Learning with R can start with the fundamentals first. Once you have mastered the basics you can move on to the advanced topics.

### How long does it take to finish the Introduction to Machine Learning with R?

The Introduction to Machine Learning with R course consists of 10 hours of video content that will help you gain a thorough understanding.

### Is Machine Learning with R easy to learn?

The videos that you find as a part of the Introduction to Machine Learning with R course are created by mentors who are industry leaders with vast experience in the field. They are aware of the needs of different learners and have designed the course to be easy to learn.

### Can I complete this Machine Learning with R course in 90 days?

Yes, you can complete the Machine Learning with R course within 90 days.

### Will I get a certificate after completing the free Machine Learning with R course?

Yes, You will receive a Course Completion Certificate from SkillUp upon completing the free Machine Learning with R program. You can unlock it by logging in to your SkillUp account. As soon as the certificate is unlocked, you will receive a mail with a link to your SkillUp learning dashboard on your registered mail address. Click the link to view and download your certificate. You can even add the certificate to your resume and share it on social media platforms.

- Disclaimer
- PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.
- *According to Simplilearn survey conducted and subject to terms & conditions with Ernst & Young LLP (EY) as Process Advisors