R Language for Data Science: from Zero to Advanced in 6 hrs | Isaias Lira | Skillshare

# R Language for Data Science: from Zero to Advanced in 6 hrs

#### Isaias Lira, Data Science and Specialist in Statistic

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58 Lessons (6h 11m)
• 1. Abertura R

6:23
• 2. Lecture 1 Course overview

3:43
• 3. Lecture 2 Some Advantages of Using R

6:49
• 4. Lecture 3 Installing the R

2:17
• 5. Lecture 4 Installing the RStudio

8:52
• 6. Lecture 5 Citing the R and some demonstrations

4:43
• 7. Lecture 6 R as calculator

5:17
• 8. Lecture 7 Introduction to objects

1:16
• 9. Lecture 8 Vector Creation

8:49
• 10. Lecture 9 Accessing and modifying the Vector (part 1)

6:57
• 11. Lecture 10 Accessing and modifying the Vector (part 2)

3:50
• 12. Lecture 11 Vector Operations (part 1)

7:28
• 13. Lecture 12 Vector Operations (part 2)

8:57
• 14. Lecture 13 Creating Sequences

4:02
• 15. Lecture 14 Sequences using Repetitions (part 1)

6:00
• 16. Lecture 15 Sequences using Repetitions (part 2)

1:53
• 17. Lecture 16 Sequences using Random Samples

9:08
• 18. Lecture 17 Creation of matrices (part 1)

4:12
• 19. Lecture 18 Creation of matrices (part 2)

1:28
• 20. Lecture 19 Matrices using the command matrix ()

5:41
• 21. Lecture 20 Accessing matrix elements

6:51
• 22. Lecture 21 Modifying Matrix Elements (Part 1)

6:35
• 23. Lecture 22 Modifying Matrix Elements (part 2)

1:37
• 24. Lecture 23 Matrix Operations

6:33
• 25. Lecture 24 Matrix Curiosities (part 1)

9:56
• 26. Lecture 25 Matrix Curiosities (part 2)

4:19
• 27. Lecture 26 Creating Arrays (part 1)

4:28
• 28. Lecture 27 Creating Arrays (part 2)

6:07
• 29. Lecture 28 Creating Arrays (part 3)

9:10
• 30. Lecture 29 Accessing Array Elements (Part 1)

6:32
• 31. Lecture 30 Accessing Array Elements (part 2)

4:33
• 32. Lecture 31 Modifying Array Elements

4:54
• 33. Lecture 32 Operations with Arrays (part 1)

9:06
• 34. Lecture 33 Operations with Arrays (part 2)

4:39
• 35. Lecture 34 Operations with Arrays (part 3)

9:54
• 36. Lecture 35 Creation of Factors

10:59
• 37. Lecture 36 Creating Lists

16:26
• 38. Lecture 37 Accessing List Information

8:40
• 39. Lecture 38 Modifying List Items

6:41
• 40. Lecture 39 Adding and Removing List Items

4:24
• 41. Lecture 40 Combining Lists

3:52
• 42. Lecture 41 Creating a DataFrame

7:01
• 43. Lecture 42 Accessing Dataframe Elements

6:01
• 44. Lecture 43 Modifying Dataframe Elements

4:29
• 45. Lecture 44 Adding and Removing Variables in the DataFrame

4:53
• 46. Lecture 45 Adding and Removing Cases in the DataFrame

8:19
• 47. Lecture 46 Logical Operators in R

9:54
• 48. Lecture 47 Loops using for ()

11:04
• 49. Lecture 48 Loops using while()

9:01
• 50. Lecture 49 Decision Making in R

7:49
• 51. Criando funĆ§Ćµes

5:38
• 52. Project (part 1)

6:27
• 53. Project (part 2)

5:14
• 54. Project (part 3)

3:23
• 55. Project (part 4)

10:31
• 56. Project (part 5)

2:56
• 57. Project (part 6)

6:36
• 58. R para ETL parte 1

7:25

Hello!!! Are you all right?

My name is IsaĆ­as M. Lira, I am a Bachelor in Statistics, a Higher Education Specialist and a Consultant in Data Analysis and I really want Statistics to stop being a problem for you and become a new SKILL for your professional career ... Come on?!!

Why did I create this course?

Data Scientist has been ranked as the first job on Glassdoor and the average salary of a data scientist is more than \$ 120,000 in the United States and is arguably the job with vacancies left over and without people able to fill it. It is the most valuable career at the moment, because it allows solving some of the most interesting problems in the world.

And if you already program in another language, know that the main language for Data Scientist is R for being free, complete, supporting large masses of data and having integrations with almost everything (SQL, Power BI, Java, etc). Why not take this big leap into Data Science?

These classes are worth thousands of dollars, but now you can learn all this information for a symbolic price!

With lots of video content, multiple exercises, simplified didactics and innovative approach, this class has made it one of the most in depth and most sought after for data science and machine learning on the internet!

Let's teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R!

This course is different because it is the simplest in this theme! It truly is a step-by-step for anyone who wants to start from scratch to the point of doing data analysis using R independently, without depending on others.

It is a 100% practical course, where you will:

1 - Starting from absolute zero (zero knowledge about programming, zero knowledge about Statistics, zero knowledge about mathematics) ...

2 - Evolve each class with real-life analytical challenges ...

3 - Until you reach an advanced level in R.

This way, even if you are terrified of numbers, you will succeed in this course!

I can not wait to see you in class ...

Register for the course and become a data scientist today! What do you have to lose?

Strong hug and I look forward to meeting you!