Data Science and Machine Learning Bootcamp with R

About Course

This **free** Data Science and Machine Learning Bootcamp with R course from Udemy will teach you how to become a data scientist. Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed. This comprehensive course covers everything from programming with R to advanced machine learning techniques, including linear regression, k nearest neighbors, k means clustering, decision trees, random forests, neural nets, deep learning, and support vector machines. It’s perfect for beginners with no programming experience or experienced developers looking to make the jump to data science. Enroll today and start your journey to becoming a data scientist.

This course includes:

Over 100 HD video lectures
Detailed code notebooks for every lecture
Programming with R
Advanced R Features
Using R Data Frames to solve complex tasks
Use R to handle Excel Files
Web scraping with R
Connect R to SQL
Use ggplot2 for data visualizations
Use plotly for interactive visualizations
Machine Learning with R

Get started with this **free** course today! You can find this and other top-rated courses on Theetay from platforms like Udemy, Udacity, Coursera, MasterClass, NearPeer, and more.

Course Content

Course Introduction

A Message from the Professor
Introduction to Course

02:34
Course Curriculum

02:02
What is Data Science

03:50

Windows Installation Set-Up

Mac OS Installation Set-Up

Development Environment Overview

Introduction to R Basics

Introduction to R Basics

02:27
Arithmetic in R

04:30
Variables

05:25
R Basic Data Types

05:31
Vector Basics

07:35
Vector Operations

04:23
Comparison Operators

06:31
Vector Indexing and Slicing

09:36
Getting Help with R and RStudio

02:12
R Basics Training Exercise

02:13
R Basics Training Exercise – Solutions Walkthrough

07:21

R Matrices

R Data Frames

R Lists

Data Input and Output with R

R Programming Basics

Introduction to Programming Basics

00:58
Logical Operators

08:05
if else and else if Statements

15:00
Conditional Statements Training Exercise

01:27
Conditional Statements Training Exercise – Solutions Walkthrough

12:05
While Loops

06:53
For Loops

12:28
Functions

19:15
Functions Training Exercise

02:14
Functions Training Exercise – Solutions

20:15

Advanced R Programming

Data Manipulation with R

Data Visualization with R

Overview of ggplot2

06:43
Histograms

18:37
Scatterplots

17:00
Barplots

07:57
Boxplots

07:02
2 Variable Plotting

07:48
Coordinates and Faceting

10:47
Themes

05:23
ggplot2 Exercises

02:29
ggplot2 Exercise Solutions

12:51

Data Visualization Project

Interactive Visualizations with Plotly

Capstone Data Project

Introduction to Machine Learning with R

Machine Learning with R – Linear Regression

Machine Learning Project – Linear Regression

Machine Learning with R – Logistic Regression

Machine Learning Project – Logistic Regression

Machine Learning with R – K Nearest Neighbors

Machine Learning Project – K Nearest Neighbors

Machine Learning with R – Decision Trees and Random Forests

Machine Learning Project – Decision Trees and Random Forests

Machine Learning with R – Support Vector Machines

Machine Learning Project – Support Vector Machines

Machine Learning with R – K-means Clustering

Machine Learning Project – K-means Clustering

Machine Learning with R – Natural Language Processing

Machine Learning with R – Neural Nets

Machine Learning Project – Neural Nets

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About Course

What Will You Learn?

Course Content

Course Introduction

A Message from the Professor

Introduction to Course

Course Curriculum

What is Data Science

Windows Installation Set-Up

Windows Installation Procedure

Mac OS Installation Set-Up

Mac OS Installation Procedure

Development Environment Overview

Development Environment Overview

Course Notes

Guide to RStudio

Introduction to R Basics

Introduction to R Basics

Arithmetic in R

Variables

R Basic Data Types

Vector Basics

Vector Operations

Comparison Operators

Vector Indexing and Slicing

Getting Help with R and RStudio

R Basics Training Exercise

R Basics Training Exercise – Solutions Walkthrough

R Matrices

Introduction to R Matrices

Creating a Matrix

Matrix Arithmetic

Matrix Operations

Matrix Selection and Indexing

Factor and Categorical Matrices

Matrix Training Exercise

Matrix Training Exercises – Solutions Walkthrough

R Data Frames

Introduction to R Data Frames

Data Frame Basics

Data Frame Indexing and Selection

Overview of Data Frame Operations – Part 1

Overview of Data Frame Operations – Part 2

Data Frame Training Exercise

Data Frame Training Exercises – Solutions Walkthrough

R Lists

List Basics

Data Input and Output with R

Introduction to Data Input and Output with R

CSV Files with R

Excel Files with R

SQL with R

Web Scraping with R

R Programming Basics

Introduction to Programming Basics

Logical Operators

if else and else if Statements

Conditional Statements Training Exercise

Conditional Statements Training Exercise – Solutions Walkthrough

While Loops

For Loops

Functions

Functions Training Exercise

Functions Training Exercise – Solutions

Advanced R Programming

Introduction to Advanced R Programming

Built-in R Features

Apply

Math Functions with R

Regular Expressions

Dates and Timestamps

Data Manipulation with R

Data Manipulation Overview

Guide to Using Dplyr

Guide to Using Dplyr – Part 2

Pipe Operator

Dplyr Training Exercise

Dplyr Training Exercise – Solutions Walkthrough

Guide to Using Tidyr

Data Visualization with R