An Introduction to R for Data Science | Introduction to R Programming - R Programming Data Science | Experfy

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Instructor

Kirill Eremenko

Data Scientist & Forex Systems Expert

My name is Kirill Eremenko and I am a Data Scientist with over 6 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.

Instructor: Kirill Eremenko

Learn Programming In R And R-Studio. Data Science, Packages, Functions, GGPlot2.

Learn R programming by doing!
Real-life analytical challenges and exercises
Instructor has 6 years of hands-on data science experience serving companies like Deloitte and Sunsuper

Duration: 10h 17m

About Course
Prerequisites
Curriculum
Reviews

Course 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!

What am I going to get from this course?

Prerequisites and Target Audience

What will students need to know or do before starting this course?

This course has been designed for all skill levels. You do not need any programming skills for this course.

Who should take this course? Who should not?

Anyone interested in learning R!

Curriculum

Module 1: Module 1

20:46

Lecture 1 Welcome to the R Programming Course!

05:46

Lecture 2 Installing R and R Studio (MAC & Windows)

07:02

Lecture 3 Exercise - Get Excited!

07:58

Module 2: Core Programming Principles

01:19:05

Lecture 4 Welcome to this section. This is what you will learn!

01:11

Lecture 5 Types of variables

10:10

Lecture 6 Using Variables

10:23

Lecture 7 Logical Variables and Operators

07:42

Lecture 8 The "While" Loop

07:24

Lecture 9 Using the console

03:56

Lecture 10 The "For" Loop

05:29

Lecture 11 The "If" statement

12:15

Lecture 12 Section Recap

05:22

Lecture 13 HOMEWORK: Law of Large Numbers

15:13

Quiz 1 Core Programming Principles

Module 3: Fundamentals Of R

01:32:33

Lecture 14 Welcome to this section. This is what you will learn!

01:04

Lecture 15 What is a Vector?

04:17

Lecture 16 Let's create some vectors

13:12

Lecture 17 Using the [] brackets

10:31

Lecture 18 Vectorized operations

05:49

Lecture 19 The power of vectorized operations

16:22

Lecture 20 Functions in R

17:58

Lecture 21 Packages in R

09:19

Lecture 22 Section Recap

06:19

Lecture 23 HOMEWORK: Financial Statement Analysis

07:42

Quiz 2 Fundamentals of R

Module 4: Matrices

01:50:28

Lecture 24 Welcome to this section. This is what you will learn!

01:10

Lecture 25 Project Brief: Basketball Trends

09:22

Lecture 26 Matrices

06:30

Lecture 27 Building Your First Matrix

13:41

Lecture 28 Naming Dimensions

03:34

Lecture 29 Colnames() and Rownames()

10:02

Lecture 30 Matrix Operations

06:12

Lecture 31 Visualizing With Matplot()

11:42

Lecture 32 Subsetting

09:20

Lecture 33 Visualizing Subsets

04:13

Lecture 34 Creating Your First Function

08:47

Lecture 35 Basketball Insights

12:38

Lecture 36 Section Recap

06:04

Lecture 37 HOMEWORK: Basketball Free Throws

07:13

Quiz 3 Matrices

Module 5: Data Frames

01:41:03

Lecture 38 Welcome to this section. This is what you will learn!

01:47

Lecture 39 Project Brief: Demographic Analysis

04:16

Lecture 40 Importing data into R

05:52

Lecture 41 Exploring your dataset

10:18

Lecture 42 Using the $ sign

06:23

Lecture 43 Basic operations with a Data Frame

09:47

Lecture 44 Filtering a Data Frame

09:04

Lecture 45 Introduction to qplot

09:09

Lecture 46 Visualizing With Qplot: Part I

06:22

Lecture 47 Building Dataframes

10:02

Lecture 48 Merging Data Frames

07:38

Lecture 49 Visualizing With Qplot: Part II

06:50

Lecture 50 Section Recap

07:19

Lecture 51 HOMEWORK: World Trends

06:16

Quiz 4

Module 6: Advanced Visualization With GGPlot2

02:06:38

Lecture 52 Welcome to this section. This is what you will learn!

01:23

Lecture 53 Project Brief: Movie Ratings

04:02

Lecture 54 Grammar Of Graphics - GGPlot2

11:26

Lecture 55 What is a Factor?

07:13

Lecture 56 Aesthetics

06:54

Lecture 57 Plotting With Layers

05:18

Lecture 58 Overriding Aesthetics

07:49

Lecture 59 Mapping vs Setting

08:09

Lecture 60 Histograms and Density Charts

07:08

Lecture 61 Starting Layer Tips

08:41

Lecture 62 Statistical Transformations

10:38

Lecture 63 Using Facets

09:30

Lecture 64 Coordinates

10:28

Lecture 65 Perfecting By Adding Themes

11:04

Lecture 66 Section Recap

09:50

Lecture 67 HOMEWORK: Movie Domestic % Gross

07:05

Quiz 5 Advanced Visualization With GGPlot2

Module 7: Advanced Visualization With GGPlot2

01:26:07

Lecture 68 Homework Solution Section 2: Law Of Large Numbers

12:01

Lecture 69 Homework Solution Section 3: Financial Statement Analysis

18:35

Lecture 70 Homework Solution Section 4: Basketball Free Throws

16:11

Lecture 71 Homework Solution Section 5: World Trends

16:30

Lecture 72 Homework Solution Section 6: Movie Domestic % Gross - Part i

11:41

Lecture 73 Homework Solution Section 6: Movie Domestic % Gross - Part ii

11:09

Reviews

13 Reviews

Swapnil P

August, 2017

Excellent introductory course of R!! Great class that helps you not just as an intro to R programming but helps you become an intermediate level user!

Sumit J

August, 2017

I highly recommend it if this is the field you're considering to get into or the skill you wish to include to your resume. It is a good start for us to learn R programming. However the course has an excellent content for both novice and experts alike. The lectures by the instructor were absolutely terrific.

Joe B

August, 2017

A very good analysis. The teaching style is very clear. You can learn R programming by doing after you have followed this program. There are lots of R courses in the market, but this course is definitely different from others as pointed out by the instructor.

Mark B

August, 2017

A good course to learn programming in R. This course has obviously improved my style of looking into data and the process we interpret it. I am looking forward to go on and take more courses to become a data scientist.

Manoj P

February, 2018

Srinivas A

January, 2018

Shabana P

December, 2017

Sandra B

April, 2018

Course felt thorough and well explained.

James G

January, 2019

Saad A

May, 2019

Provides comprehensive start for beginners

Ingrid D

October, 2017

Courses that state that they are “simple” are usually either: a) too simple or b) too complicated, but the instructor “thinks” otherwise. This course, however, is neither! A great approach to learning R, step by step, filled with tons of examples that made sure I understood everything inside. Overall: fantastic course!

Erik L

October, 2017

If you’re on the edge about learning R, then this is the course for you! Great lessons, explanations, and examples that truly take you one step at a time from zero to master! Also, a lot of content for such a price! Highly recommend it!

Saad A

May, 2019

Provides comprehensive start for beginners