Getting Started with Machine Learning with R
Getting Started with Machine Learning with R
Unleash the powerful capabilities of R to work effectively with data
About This Getting Started with R for Data Science Video course
- Find out how to load, analyze, and manipulate data from large datasets to make informed decisions
- Be introduced to RStudio, R programming, as well as the tools available to mine data from social media
- A tutorial with hands-on working examples of R programming
R for DataScience In Detail
The R language is a powerful open source functional programming language. R is becoming the go-to tool for data scientists and analysts. Its growing popularity is due to its open source nature and extensive development community.
This video course will take you on a journey to become an efficient data science practitioner as you thoroughly understand the key concepts of R. Starting from the absolute basics, you will quickly be introduced to programming in R.
You will see how to load data into R for analysis, and get a good understanding of how to write R scripts. We will delve into data types in R, and you'll gain the ability to read and write data to and from databases as well as files. You will also get to know how to perform basic analysis of the data.
By the end of the course, you will know how data science can be applied in practical conditions.
What will you learn in this course?
Course plan
Chapter 1
Introducing R
Introducing R
Chapter 2
Getting Data into R
Getting Data into R
Chapter 3
Cleaning and Blending Data
Cleaning and Blending Data
Chapter 4
Cooking the Codebook
Cooking the Codebook
Chapter 5
Data Mining and Analysis
Data Mining and Analysis
Chapter 6
A Picture Paints a Thousand Words
A Picture Paints a Thousand Words
Detailed course plan
Chapter 1 : Introducing R
21m11
Lesson 1The Course Overview
Lesson 2What is R?
Lesson 3The Structure of the Language
Lesson 4Data Structures within R
Lesson 5Writing a Simple Program in R
Chapter 2 : Getting Data into R
18m14
Lesson 1The Structure of a DataFrame
Lesson 2Creating a DataFrame from a CSV File
Lesson 3Creating a DataFrame from a Zip File
Lesson 4Creating a DataFrame from a Database
Chapter 3 : Cleaning and Blending Data
18m28
Lesson 1The Tools Available for Cleaning Data
Lesson 2Dealing with Null Values
Lesson 3Standardizing Date Formats
Lesson 4Blending Multiple DataFrames
Chapter 4 : Cooking the Codebook
09m50
Lesson 1What Is a Codebook and Why Create One?
Lesson 2Creating the Codebook Using Standard R API Functionality
Lesson 3Manually Creating a Custom Codebook
Chapter 5 : Data Mining and Analysis
17m06
Lesson 1Introduction to Data Mining and Analysis
Lesson 2The Tools and Techniques for Creating the Story
Lesson 3Regression Analysis with R
Lesson 4Clustering Data with R
Lesson 5Classifying Data with R
Chapter 6 : A Picture Paints a Thousand Words
14m15
Lesson 1Data Visualization Tools
Lesson 2Creating Static Visualization Plots
Lesson 3Creating Interactive Plots
Lesson 4Publishing the Graphics
Lesson 5What's Next?
