Data Science: R Programming For Data Science Complete Bootcamp

Hello and Welcome to the exciting world of the R programming language.

# Data Science: The R Programming For Data Science Complete Bootcamp 2024

R is one of the most powerful programming languages, for statistical computing and graphical presentation to analyze and visualize data.

In this course, I’m going to show you how to code with R from the R basics to the R advanced concepts.

Also, you will explore how the R programming language can be used today for data analysis and the production of beautiful data visualizations and graphics.

The best part? Every single topic and tool in this course will be explained theoretically and practically with real examples step by step.

What you'll learn

• The R working tools and environment for professionals

• The R syntax and how to explain and describe the code using comments

• Variables, Values and assignments

• All the Data types available in R

• Performing mathematical operations, type conversion built-in functions and many useful built-in functions for math operations

• Working with collection of characters and strings in R, also essential character operations

• Logical values and booleans

• Handling different operations on variables and values by using different types of operators

• All the Data Structures in R such as vectors, lists, matrices, data frames and factors. And also all the essential operations for these data structures

• Decision making by using conditional statements in R

• Repeat block of code and iterate over collections with loops

• Functional programming and code reusing

• Statistics and data analysis concepts: datasets, many built-in functions, techniques and tools for statistical operations

• Data visualizations and Graphics in R: drawing points, line plotting, pie charts, bar charts, histograms and more

• Get the instructor QA Support

# Reviews about this course

★★★★★ "easy to understand, teaching good."

★★★★★ "It’s really good. I’m just pumped to learn as much as I can"

Reed courses certificate of completion

Digital certificate - Included

• Module 0: Introduction 16:20

  • 1: Intro to course 04:03
  • 2: Downloading and Installing R 05:05
  • 3: Downloading and Installing the RStudio IDE 06:04
  • 4: Setup working directory 01:08

• Module 1: Variables, Data Types and Hints 23:56

  • 5: Variables in detail 1 03:00
  • 6: Variables in detail 2 03:57
  • 7: Variables in detail 3 03:21
  • 8: Variables in detail 4 02:45
  • 9: Data Types 1 02:44
  • 10: Data Types 2 03:17
  • 11: Data Types 3 02:41
  • 12: Code hints 02:11

• Module 2: Numbers and Math 24:58

  • 13: Type of numbers 08:12
  • 14: Type Conversion 07:36
  • 15: Math operations 09:10

• Module 3: Characters 16:41

  • 16: Strings 1 03:30
  • 17: Strings 2 02:49
  • 18: Strings 3 03:06
  • 19: Strings 4 01:37
  • 20: Strings 5 01:52
  • 21: Strings 6 01:13
  • 22: Strings 7 02:34

• Module 4: Logical and operators 18:56

  • 23: Logical values 1 01:19
  • 24: Logical values 2 04:11
  • 25: Operators 1 01:46
  • 26: Operators 2 03:34
  • 27: Operators 3 02:15
  • 28: Operators 4 02:23
  • 29: Operators 5 03:28

• Module 5: DS - Vectors 20:45

  • 30: Vectors 1 01:32
  • 31: Vectors 2 03:29
  • 32: Vectors 3 03:21
  • 33: Vectors 4 03:17
  • 34: Vectors 5 04:17
  • 35: Vectors 6 02:54
  • 36: Vectors 7 01:55

• Module 6: DS - Lists 16:45

  • 37: Lists 1 02:44
  • 38: Lists 2 04:27
  • 39: Lists 3 04:54
  • 40: Lists 4 04:40

• Module 7: DS - Matrices 18:37

  • 41: DS - Matrices 1 01:19
  • 42: DS - Matrices 2 03:27
  • 43: DS - Matrices 3 04:54
  • 44: DS - Matrices 4 06:54
  • 45: DS - Matrices 5 02:03

• Module 8: DS - Arrays 12:13

  • 46: DS - Arrays 1 00:50
  • 47: DS - Arrays 2 02:00
  • 48: DS - Arrays 3 01:56
  • 49: DS - Arrays 4 03:35
  • 50: DS - Arrays 5 03:52

• Module 9: DS - Data Frame 18:20

  • 51: DS - Data Frame 1 01:36
  • 52: DS - Data Frame 2 03:05
  • 53: DS - Data Frame 3 02:36
  • 54: DS - Data Frame 4 05:06
  • 55: DS - Data Frame 5 02:55
  • 56: DS - Data Frame 6 03:02

• Module 10: DS - Factors 12:54

  • 57: DS - Factors 1 01:16
  • 58: DS - Factors 2 05:33
  • 59: DS - Factors 3 02:24
  • 60: DS - Factors 4 03:41

• Module 11: Decision making 12:02

  • 61: Conditional statements 1 02:18
  • 62: Conditional statements 2 03:29
  • 63: Conditional statements 3 02:28
  • 64: Conditional statements 4 03:47

• Module 12: Repetition 20:17

  • 65: While loop 1 01:47
  • 66: While loop 2 03:47
  • 67: While loop 3 02:54
  • 68: For loop 1 01:22
  • 69: For loop 2 02:31
  • 70: For loop 3 05:37
  • 71: For loop 4 02:19

• Module 13: Functional Programming 18:25

  • 72: Functions 1 01:11
  • 73: Functions 2 03:08
  • 74: Functions 3 05:21
  • 75: Functions 4 02:58
  • 76: Functions 5 05:47

• Module 14: Statistics and Data analysis 20:21

  • 77: Statistics and data analysis 1 01:53
  • 78: Statistics and data analysis 2 08:27
  • 79: Statistics and data analysis 3 03:42
  • 80: Statistics and data analysis 4 03:42
  • 81: Statistics and data analysis 5 02:37

• Module 15: Data Visualization and Graphics 35:55

  • 82: Plotting in R 1 00:37
  • 83: Plotting in R 2 04:52
  • 84: Plotting in R 3 03:25
  • 85: Plotting in R 4 01:57
  • 86: Lines 1 00:44
  • 87: Lines 2 03:21
  • 88: Lines 3 03:15
  • 89: Pie Charts 1 00:32
  • 90: Pie Charts 2 02:57
  • 91: Pie Charts 3 05:03
  • 92: bars and histograms 1 01:11
  • 93: bars and histograms 2 02:05
  • 94: bars and histograms 3 01:34
  • 95: bars and histograms 4 02:00
  • 96: bars and histograms 5 02:22

This course will cover all the R fundamentals needed such as:

• The R working tools and environment for professionals

• The R syntax and how to explain and describe the code using comments

• Variables, Values and assignments

• All the Data types available in R.

• Performing mathematical operations, type conversion built-in functions and many useful built-in functions for math operations.

• Working with collection of characters and strings in R, also essential character operations

• Logical values and Booleans.

• Handling different operations on variables and values by using different types of operators.

• All the Data Structures in R such as vectors, lists, matrices, data frames and factors

  And also all the essential operations for these data structures.

• decision making by using conditional statements in R.

• Repeat block of code and iterate over collections with loops.

• Functional programming and code reusing.

• Statistics and data analysis concepts: datasets, many built-in functions, techniques and tools for statistical operations.

• Graphics and data visualizations in R: drawing points, line plotting, pie charts, bar charts, histograms and more.

You will learn and understand all these concepts and more.

R is free open source, and very widely used by professional statisticians and data scientists.

It is also very popular in certain application areas, including bioinformatics. R is a dynamically typed interpreted language, and is typically used interactively. It has many built-in functions and libraries, and is extensible, allowing users to define their own functions and procedures using R, C or Fortran. It also has a simple object system. So, it's really powerful!

So, what are you waiting for, enroll now to go through a complete bootcamp of one of the most popular and powerful programming languages on the market for , R.

Become A Professional R Programmer and Data Scientist in no time!

Let's get started

• Beginner R Programmers
• New developers and Engineers
• Programming and software development engineering newbies
• Developers and Engineers who know other programming language but are new to R
• Developers curious about Learning R for data science
• Beginner Data Engineers/Scientists

• No programming experience needed. You'll learn everything you need to know.

• Desire to learn R programming.

1. Data Science Foundations
2. Math and Statistics
3. R Programming for Data Analysis and Data Visualization
4. Building Projects with R

• The average annual pay for a R Programmer is $90,940 a year.
• The average annual pay for a R Developer is $130,327 a year.
• The average annual pay for a Remote R Programmer is $90,665 a year.
• The average annual pay for a Data Analyst Programmer is $79,345 a year.