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! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!
This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!
We’ll teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R! Here a just a few of the topics we will be learning:
 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, including:
 Linear Regression
 K Nearest Neighbors
 K Means Clustering
 Decision Trees
 Random Forests
 Data Mining Twitter
 Neural Nets and Deep Learning
 Support Vectore Machines
 and much, much more!
Enroll in the course and become a data scientist today!
Course Best Practices
Windows Installation SetUp
Mac OS Installation SetUp
Linux Installation
Development Environment Overview
Introduction to R Basics
R Matrices

14Introduction to R Basics
Introduction to R Basics Section

15Arithmetic in R
Learn how to use R as a calculator!

16Variables
Learn how to use Variables in R!

17R Basic Data Types
Learn about RÂ Data Types

18Vector Basics
Learn about Vectors in R!

19Vector Operations
Learn aboutÂ Vector Operations!

20Comparison Operators
Learn about Comparison Operators

21Vector Indexing and Slicing
Learn how to index and slice data from vectors!

22Getting Help with R and RStudio
Learn how to get help from within R and RStudio!

23R Basics Training Exercise
Overview of Training Exercise

24R Basics Training Exercise  Solutions Walkthrough
Solutions to Training Exercise
R Data Frames

25Introduction to R Matrices
Introduction to RÂ Matrices!

26Creating a Matrix
Learn how to create a matrix in R!

27Matrix Arithmetic
Learn about Matrix Arithmetic!

28Matrix Operations
Learn about Matrix Operations in R!

29Matrix Selection and Indexing
Learn how to grab data from a Matrix!

30Factor and Categorical Matrices
Learn about Factor and Categorical Matrices!

31Matrix Training Exercise
Overview of Training Exercise

32Matrix Training Exercises  Solutions Walkthrough
Solutions to theÂ Training Exercise
R Lists

33Introduction to R Data Frames
Introduction to RÂ DataÂ Frames!

34Data Frame Basics
Learn the Basics of Data Frames in R!

35Data Frame Indexing and Selection
Learn how to grab data from a Data Frame in R!

36Overview of Data Frame Operations  Part 1
Get an overview of the variety of operations you can use on a Data Frame in R!

37Overview of Data Frame Operations  Part 2
Get an overview of the variety of operations you can use on a Data Frame in R!

38Data Frame Training Exercise
Overview of Training Exercise

39Data Frame Training Exercises  Solutions Walkthrough
Solutions to theÂ Training Exercise
Data Input and Output with R
R Programming Basics

41Introduction to Data Input and Output with R
Learn how to input and export data in R!

42CSV Files with R
Learn how to work with CSV files in R!

43Note on R with Excel Download

44Excel Files with R
Learn how to work with Excel Files in R!

45SQL with R
Learn about your various options for SQL and R!

46Web Scraping with R
Learn about rvest and webscraping with R!
Advanced R Programming

47Introduction to Programming Basics
Intro to Programming Basics

48Logical Operators
Learn about Logical Operators!

49if, else, and else if Statements
Learn about if, else, and else if Statements in R!

50Conditional Statements Training Exercise
Overview of Training Exercise

51Conditional Statements Training Exercise  Solutions Walkthrough
Solutions to theÂ Training Exercise

52While Loops
Learn about While Loops in R!

53For Loops
Learn about For Loops in R!

54Functions
Learn how to create functions in R!

55Functions Training Exercise
Test your functions knowledge!

56Functions Training Exercise  Solutions
Solutions to theÂ Training Exercise
Data Manipulation with R

57Introduction to Advanced R Programming
Intro to Advanced R Programming Section!

58Builtin R Features
Learn about Builtin R Features!

59Apply
Learn how to use the Apply family of functions in R!

60Math Functions with R
Learn about various Math Functions in R!

61Regular Expressions
Learn about Regular Expressions and Pattern Recognition in R!

62Dates and Timestamps
Learn about Dates and Timestamps in R!
Data Visualization with R

63Data Manipulation Overview
Overview of Dplyr and Tidyr

64Guide to Using Dplyr
Get a guide to using Dplyr in R

65Guide to Using Dplyr  Part 2
Part 2 of Guide to using Dplyr in R!

66Pipe Operator
Pipe Operator

67Quick note on Dpylr exercise
Quick note

68Dplyr Training Exercise
Overview of Training Exercise

69Dplyr Training Exercise  Solutions Walkthrough
Solutions to theÂ Training Exercise

70Guide to Using Tidyr
Guide to using Tidyr in R!
Data Visualization Project

71Overview of ggplot2
Learn about Data Visualization in R with ggplot2!

72Histograms
Learn about Data Visualization in R with ggplot2!

73Scatterplots
Learn about Data Visualization in R with ggplot2!

74Barplots
Learn about Data Visualization in R with ggplot2!

75Boxplots
Learn about Data Visualization in R with ggplot2!

762 Variable Plotting
Learn about Data Visualization in R with ggplot2!

77Coordinates and Faceting
Learn about Data Visualization in R with ggplot2!

78Themes
Learn about Data Visualization in R with ggplot2!

79ggplot2 Exercises
Intro to exercises for ggplot2!

80ggplot2 Exercise Solutions
Walkthrough for the Solutions to the ggplot2 Exercise Questions!