R Programming A-Z™: R For Data Science With Real Exercises! | Kirill Eremenko | Skillshare

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R Programming A-Z™: R For Data Science With Real Exercises!

teacher avatar Kirill Eremenko, Data Scientist

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Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Lessons in This Class

74 Lessons (10h 19m)
    • 1. Intro

    • 2. Welcome to the R Programming Course!

    • 3. Installing R and R Studio (MAC & Windows)

    • 4. Exercise - Get Excited!

    • 5. Welcome to the CORE PROGRAMMING SECTION section. This is what you will learn!

    • 6. Types of variables

    • 7. Using Variables

    • 8. Logical Variables and Operators

    • 9. The "While" Loop

    • 10. Using the console

    • 11. The "For" Loop

    • 12. The "If" statement

    • 13. Section Recap

    • 14. HOMEWORK: Law of Large Numbers

    • 15. Welcome to Fundamentals of R SECTION

    • 16. What is a Vector?

    • 17. Let's create some vectors

    • 18. Using the [] brackets

    • 19. Vectorized operations

    • 20. The power of vectorized operations

    • 21. Functions in R

    • 22. Packages in R

    • 23. Section Recap

    • 24. HOMEWORK: Financial Statement Analysis

    • 25. Welcome to the MATRICIES section. This is what you will learn!

    • 26. Project Brief: Basketball Trends

    • 27. Matrices

    • 28. Building Your First Matrix

    • 29. Naming Dimensions

    • 30. Colnames() and Rownames()

    • 31. Matrix Operations

    • 32. Visualizing With Matplot()

    • 33. Subsetting

    • 34. Visualizing Subsets

    • 35. Creating Your First Function

    • 36. Basketball Insights

    • 37. Section Recap

    • 38. HOMEWORK: Basketball Free Throws

    • 39. Welcome to the DATA FRAMES section. This is what you will learn!

    • 40. Project Brief: Demographic Analysis

    • 41. Importing data into R

    • 42. Exploring your dataset

    • 43. Using the $ sign

    • 44. Basic operations with a Data Frame

    • 45. Filtering a Data Frame

    • 46. Introduction to qplot

    • 47. Visualizing With Qplot: Part I

    • 48. Building Dataframes

    • 49. Merging Data Frames

    • 50. Visualizing With Qplot: Part II

    • 51. Section Recap

    • 52. HOMEWORK: World Trends

    • 53. Welcome to the ADVANCED VISUALIZATION section. This is what you will learn!

    • 54. Project Brief: Movie Ratings

    • 55. Grammar Of Graphics - GGPlot2

    • 56. What is a Factor?

    • 57. Aesthetics

    • 58. Plotting With Layers

    • 59. Overriding Aesthetics

    • 60. Mapping vs Setting

    • 61. Histograms and Density Charts

    • 62. Starting Layer Tips

    • 63. Statistical Transformations

    • 64. Using Facets

    • 65. Coordinates

    • 66. Perfecting By Adding Themes

    • 67. Section Recap

    • 68. HOMEWORK: Movie Domestic % Gross

    • 69. Homework Solution Section 2: Law Of Large Numbers

    • 70. Homework Solution Section 3: Financial Statement Analysis

    • 71. Homework Solution Section 4: Basketball Free Throws

    • 72. Homework Solution Section 5: World Trends

    • 73. Homework Solution Section 6: Movie Domestic % Gross (Part 1)

    • 74. Homework Solution Section 6: Movie Domestic % Gross (Part 2)

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About This Class

Learn R Programming by doing!

There are lots of R courses and lectures out there. However, R has a very steep learning curve and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial, we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,


Kirill Eremenko

Meet Your Teacher

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Kirill Eremenko

Data Scientist


My name is Kirill Eremenko and I am super-psyched that you are reading this!

Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.

From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.

To sum u... See full profile

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1. Intro: Let me ask you a question. Are you tired off learning our programming but never quite getting there? Are you frustrated with the books and courses that promise to teach you the language but are way over complicated? Well, in that case, welcome to the only course that will make the complex simple. My name is Carol Eremenko and I will be your instructor. So what makes this course stand up? While several things, first of all, in every single tutorial, you will learn a valuable new skill. And in every single section you will see how to apply those skills to re a world projects Next. This course is designed to take you step by step through the steep learning curve of our So you never get lost and you always feel on top of your game. And finally, this course is extremely fun because we will be using specifically designed datasets and will be an exciting way to practise the skills that you learn. And now let's have a look inside the core Suk and decide for yourself. If it's right for you in this course, we will start up with the very basics. But even then we will already learnt how to combine programming and statistical concepts. Then we will move on to more advanced topics such as matrices and daughter frames. And every time there will be ample theory as well as really live examples to support our learning. And on top of all of that, in this course, you will learn how to create the most stunning visualizations that will help you deliver your analysis and truly captivate your audience. And these are just a few examples off what we will cover inside this class. Did you like what you saw? Well, if you're interested in finally mustering our programming and skyrocketing a daughter science carrier that this is the course that you have been looking for Click to take this corresponding now and join the claws and I look forward to seeing inside. 2. Welcome to the R Programming Course!: hello and welcome to the course and our programming. I'm super excited that you decided to join. And I can promise you right now that in this course you will learn a lot and we will have tons of fun along the way. And I have designed this course specifically to address a pain point that I personally had when I was studying our programming. And that is the fact that this language has a very steep learning curve. And the courses out there just throw you in the deep end right away. And it's very hard to actually sit down and get this language going and understand it very well so that you can apply it in your work. So this course is structured differently. This course will take you step by step through everything in our and like all my other courses, you will learn gradually with lots of examples with applying your knowledge to real world problems, and you will learn a spiral structure. So everything you learn, you won't won't just move away from that in the coming tutorials. After that, we will concrete that knowledge in because we'll practice and reiterate it, and we will build on existing knowledge. So that way, everything you learn, you will get to keep and take away. After this course and what I want to do in this tutorials, I just want to quickly show you around the section of the course so you can navigate your way better. And then we will dive straight into installing are and let's jump to the presentation off the sections of the course Now. All right, so here's the course. And now if I scroll a little bit down to the sections, we will see section one here. So Section one hit the ground running here. We've got a lecture. One, which is the lecture we're in right now. Then we're going to install our in our studio and I'll show you how to do that both on Mac and PC Onda. Finally, we've got an exercise, a super quick exercise to get you excited about this course to show you all of the powerful things you will learn towards the end of the course. Yes, you will be able to already perform them there. I highly recommend doing this exercise. You will see how much power are has and then throughout the course, you'll actually learn in detail exactly what you did in a lecture. Three. So pretty interesting lecture over there. Then we've got Section two core programming principles, and here this section is designed to introduce you to programming if you've never programmed before, so feel free. Just keep it if you have programmed before, or maybe just proceed straight to the homework for this section because it's quite interesting. Is God some statistical knowledge combined of programming. If you haven't ever programmed before, then no worries. This section will get you up to speed with everything you need to know to master the rest of the course and learn our. Then we're moving onto fundamentals of our so are is a very specific type of programming language. It is old victory rised and here that's what we're going to talk about. We're going to talk about victories, operations and how to access elements of vectors, functions, packages and so on. And basically that's what the sections about. It's about the specifics off this programming language. All right, then we're moving onto matrices, so matrices are multi dimensional objects. It might be a sound like a complicated topic, but It's actually very simple and more over here. We've got a very interesting daughter, said. We're talking about basketball trends, so we're going to be looking at the top page players off the N b A. On. We're going to have a matrix. We're going to learn how to work with it At the same time, we're already going to be deriving very valuable insights, and we're gonna have a lot of fun in this section. I can't wait for you to check it out. Actually, then a Section five daughter frames. What are we talking about here? Well, daughter frames are kind of a step up from matrices, and this is the main section for daughter science. So every time you're going to be working with daughter, it's like 99% of time is gonna be a daughter from, So it's very important section to know all of this A with these things and skills that we're talking about Onda again, we're going to have a very interesting stop it. We're going to be talking about demographic analysis. We're going to be working from