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30-Day Money-Back Guarantee
Development Data Science R (Programming Language)

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

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2
Bestseller
Rating: 4.6 out of 54.6 (39,751 ratings)
204,542 students
Created by Kirill Eremenko, Ligency Team
Last updated 4/2021
English
English, French [Auto], 
30-Day Money-Back Guarantee

What you'll learn

  • Learn to program in R at a good level
  • Learn how to use R Studio
  • Learn the core principles of programming
  • Learn how to create vectors in R
  • Learn how to create variables
  • Learn about integer, double, logical, character and other types in R
  • Learn how to create a while() loop and a for() loop in R
  • Learn how to build and use matrices in R
  • Learn the matrix() function, learn rbind() and cbind()
  • Learn how to install packages in R
  • Learn how to customize R studio to suit your preferences
  • Understand the Law of Large Numbers
  • Understand the Normal distribution
  • Practice working with statistical data in R
  • Practice working with financial data in R
  • Practice working with sports data in R
Curated for the Udemy for Business collection

Course content

8 sections • 82 lectures • 10h 39m total length

  • Preview05:46
  • Updates on Udemy Reviews
    01:09
  • Installing R and R Studio (MAC & Windows)
    07:02
  • BONUS: Learning Paths
    00:34
  • Preview07:58
  • Get the materials
    00:05
  • Some Additional Resources!!
    00:13
  • Preview00:33
  • Your Shortcut To Becoming A Better Data Scientist!
    02:05

  • Welcome to this section. This is what you will learn!
    01:11
  • Types of variables
    10:10
  • Using Variables
    10:23
  • Preview07:42
  • The "While" Loop
    07:33
  • Using the console
    04:04
  • The "For" Loop
    05:29
  • The "If" statement
    12:15
  • Section Recap
    05:22
  • HOMEWORK: Law of Large Numbers
    15:13
  • Core Programming Principles
    5 questions

  • Welcome to this section. This is what you will learn!
    01:04
  • What is a Vector?
    04:17
  • Let's create some vectors
    13:12
  • Using the [] brackets
    10:31
  • Preview05:49
  • The power of vectorized operations
    16:22
  • Functions in R
    17:58
  • Packages in R
    09:19
  • Section Recap
    06:19
  • HOMEWORK: Financial Statement Analysis
    07:42
  • Fundamentals of R
    5 questions

  • Welcome to this section. This is what you will learn!
    00:52
  • Project Brief: Basketball Trends
    09:22
  • Matrices
    06:30
  • Building Your First Matrix
    13:41
  • Naming Dimensions
    03:34
  • Colnames() and Rownames()
    10:02
  • Matrix Operations
    06:12
  • Visualizing With Matplot()
    11:42
  • Subsetting
    09:20
  • Visualizing Subsets
    04:13
  • Creating Your First Function
    08:47
  • Preview12:38
  • Section Recap
    06:04
  • HOMEWORK: Basketball Free Throws
    07:13
  • Matrices
    5 questions

  • Welcome to this section. This is what you will learn!
    01:47
  • Project Brief: Demographic Analysis
    04:16
  • Importing data into R
    05:52
  • Exploring your dataset
    10:18
  • Using the $ sign
    06:23
  • Basic operations with a Data Frame
    09:47
  • Filtering a Data Frame
    09:04
  • Introduction to qplot
    09:09
  • Preview06:22
  • Building Dataframes
    10:02
  • Merging Data Frames
    07:38
  • Visualizing With Qplot: Part II
    06:50
  • Section Recap
    07:19
  • HOMEWORK: World Trends
    06:16
  • Data Frames
    5 questions

  • Welcome to this section. This is what you will learn!
    01:23
  • Project Brief: Movie Ratings
    04:02
  • Grammar Of Graphics - GGPlot2
    Preview11:26
  • What is a Factor?
    07:13
  • Aesthetics
    06:54
  • Plotting With Layers
    05:18
  • Overriding Aesthetics
    07:49
  • Mapping vs Setting
    08:09
  • Histograms and Density Charts
    07:08
  • Starting Layer Tips
    08:41
  • Statistical Transformations
    10:38
  • Using Facets
    09:30
  • Coordinates
    10:28
  • Perfecting By Adding Themes
    11:04
  • Section Recap
    09:50
  • HOMEWORK: Movie Domestic % Gross
    07:05
  • Advanced Visualization With GGPlot2
    5 questions

  • Homework Solution Section 2: Law Of Large Numbers
    12:01
  • Homework Solution Section 3: Financial Statement Analysis
    18:35
  • Homework Solution Section 4: Basketball Free Throws
    16:11
  • Homework Solution Section 5: World Trends
    16:30
  • Homework Solution Section 6: Movie Domestic % Gross (Part 1)
    11:41
  • Homework Solution Section 6: Movie Domestic % Gross (Part 2)
    11:09
  • THANK YOU bonus video
    02:40

  • BoxPlots
    13:32
  • **YOUR SPECIAL BONUS**
    01:56

Requirements

  • No prior knowledge or experience needed. Only a passion to be successful!

Description

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,

Sincerely,

Kirill Eremenko

Who this course is for:

  • This course is for you if you want to learn how to program in R
  • This course is for you if you are tired of R courses that are too complicated
  • This course is for you if you want to learn R by doing
  • This course is for you if you like exciting challenges
  • You WILL have homework in this course so you have to be prepared to work on it

Featured review

Khaled Khaled
Khaled Khaled
7 courses
5 reviews
Rating: 5.0 out of 5a year ago
I've tried several websites before to learn new programming languages and to be honest I'm already half way through the course, within days, for two main reasons: 1) The course is very interactive and expects you to code as you go. I found this to be the best way to learn. 2) The contents of the course are super fun which probably explains why I went through the course this quickly. I will definitely be doing more udemy courses based on this geat experience so far!

Instructors

Kirill Eremenko
Data Scientist
Kirill Eremenko
  • 4.5 Instructor Rating
  • 470,963 Reviews
  • 1,748,963 Students
  • 44 Courses

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 up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.5 Instructor Rating
  • 482,714 Reviews
  • 1,733,911 Students
  • 112 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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