R Programming for Complete Beginners

R Programming for Complete Beginners, available at $79.99, has an average rating of 4.5, with 106 lectures, 3 quizzes, based on 43 reviews, and has 3284 subscribers.

You will learn about The Fundamentals Concepts of R Programming in Details How to Download and Install and Use RStudio Variables and how to create them in R Create different types of Loops in R Different types of Data types in R How to Update R and RStudio What are Packages and how to install them How to Create Vectors in R How to Create Lists in R The Difference Between Directory and Projects and how to use them This course is ideal for individuals who are This course is for you if you want to learn how to R Language from Scratch or This course is for you if you want to learn R to become a Data Scientist or Data Analyst or This course is for you if you face difficulties in understanding programming concepts as everything is explained in this course in details or This course is for you if you want to learn R and you dont have a tech background, as everything is explained in layman terms or This course is for you if you want to learn By doing exercises and quizzes It is particularly useful for This course is for you if you want to learn how to R Language from Scratch or This course is for you if you want to learn R to become a Data Scientist or Data Analyst or This course is for you if you face difficulties in understanding programming concepts as everything is explained in this course in details or This course is for you if you want to learn R and you dont have a tech background, as everything is explained in layman terms or This course is for you if you want to learn By doing exercises and quizzes.

Enroll now: R Programming for Complete Beginners

Summary

Title: R Programming for Complete Beginners

Price: $79.99

Average Rating: 4.5

Number of Lectures: 106

Number of Quizzes: 3

Number of Published Lectures: 106

Number of Published Quizzes: 3

Number of Curriculum Items: 109

Number of Published Curriculum Objects: 109

Original Price: $79.99

Quality Status: approved

Status: Live

What You Will Learn

The Fundamentals Concepts of R Programming in Details

How to Download and Install and Use RStudio

Variables and how to create them in R

Create different types of Loops in R

Different types of Data types in R

How to Update R and RStudio

What are Packages and how to install them

How to Create Vectors in R

How to Create Lists in R

The Difference Between Directory and Projects and how to use them

Who Should Attend

This course is for you if you want to learn how to R Language from Scratch

This course is for you if you want to learn R to become a Data Scientist or Data Analyst

This course is for you if you face difficulties in understanding programming concepts as everything is explained in this course in details

This course is for you if you want to learn R and you dont have a tech background, as everything is explained in layman terms

This course is for you if you want to learn By doing exercises and quizzes

Target Audiences

This course is for you if you want to learn how to R Language from Scratch

This course is for you if you want to learn R to become a Data Scientist or Data Analyst

This course is for you if you face difficulties in understanding programming concepts as everything is explained in this course in details

This course is for you if you want to learn R and you dont have a tech background, as everything is explained in layman terms

This course is for you if you want to learn By doing exercises and quizzes

Are you:

1- Planning to do your Master’s or Ph.D.’s and want to learn R

2- Planning to get into the field of Data Science or Data Analytics

3- Trying to learn R and Facing difficulties in understanding it

4- A Researcher and wants to learn R

5- A Complete Beginner in the field of Programming and want to learn R

Then this course is for you

There are plenty of R Courses on this platform, but how this course is different?!

Let me tell you how the course is structured:

After every concept you learn, you will see me applying it practically on RStudio, and then there will be an exercise for you so you can apply what you learned, and then there will be a small quiz to test your knowledge and then after each section, there will be a small project (with the solution provided) so you can check your code with mine

So, the structure is like this:

1- A theory video (where I will explain the concept in detail)

2- A practical video (where I re-explain what I taught in the previous video again but this time in RStudio)

3- A small quiz to test your knowledge after every concept

4- An Assignment for you to do to test your knowledge

5- At the end of each section there might be a small project that will make sure that you have enough skills to move to the next section in the course

6- All the solutions will be provided so you can check your code with mine

As you can see that his course is a very practical course, hope you enjoy the course, just like I enjoyed creating it!!

Wish you all the best

Fahad Masood Reda

Course Curriculum

Chapter 1: Welcome to the course

Lecture 1: Course Overview

Lecture 2: (MUST WATCH) Udemy Review and Rating Policy

Lecture 3: Get to Know your Instructor

Lecture 4: Kindly Rate the Course

Lecture 5: Udemy Player Overview

Lecture 6: How the Course is Structured

Lecture 7: What Makes this Course Special (Why You Should Enroll to this Course)

Chapter 2: Getting Ready to Learn R

Lecture 1: Codes used in this course

Lecture 2: Installing R and RStudio

Lecture 3: What is R language?

Lecture 4: RStudio-Overview

Lecture 5: Checking and Setting the Directory

Lecture 6: Updating R and RStudio

Lecture 7: Changing R version

Lecture 8: Introduction to RStudio Cloud

Lecture 9: RStudio Cloud Overview

Lecture 10: Directory vs Projects – Part1

Lecture 11: Directory vs Projects – Part2

Lecture 12: Type of files in R

Lecture 13: Packages in R

Lecture 14: Running R Codes in Jupyter Notebook

Lecture 15: Jupyter Notebook Crash Course

Chapter 3: Basics of programming

Lecture 1: Topics covered in this section

Lecture 2: Variables in R

Lecture 3: Note before watching the next video

Lecture 4: Data Types in R (Theory)

Lecture 5: Data Types in R (Practice)

Lecture 6: Variables and Data Types in R (Exercise)

Lecture 7: Variables and Data Types in R (Exercise-Solution)

Lecture 8: Operators in R (Theory)

Lecture 9: Operators in R (Practice)

Lecture 10: Operators in R (Exercise)

Lecture 11: Operators in R (Exercise)

Lecture 12: Operators in R (Exercise -Solution)

Lecture 13: Loops in R (Theory)

Lecture 14: Loops in R (Practice)

Lecture 15: Loops in R (Exercise)

Lecture 16: Loops in R (Exercise)

Lecture 17: Loops in R (Exercise -Solution)

Lecture 18: IF Statement (Theory)

Lecture 19: IF Statement (Practice)

Lecture 20: IF Statement (Exercise)

Lecture 21: IF Statement (Exercise-Solution)

Lecture 22: Case Sensitive

Lecture 23: Checking Variables

Lecture 24: Data Types vs Data Structures

Lecture 25: Deleting a Variable

Lecture 26: Deleting a Variable (Exercise)

Lecture 27: Deleting a Variable (Exercise)

Lecture 28: Deleting a Variable (Exercise-Solution)

Lecture 29: Miscellaneous Operators (Theory)

Lecture 30: Correction in the previous Lecture

Lecture 31: Miscellaneous Operators (Practice)

Lecture 32: Miscellaneous Operators (Exercise)

Lecture 33: Miscellaneous Operators (Exercise -Solution)

Chapter 4: Basics of R Programming

Lecture 1: Introduction to Basics of R Programming Section

Lecture 2: Data Structures in R

Lecture 3: Vectors in R (Theory)

Lecture 4: Vectors in R (Practice)

Lecture 5: Vectors in R (Exercise)

Lecture 6: Vectors in R (Solution)

Lecture 7: Lists in R (Theory)

Lecture 8: Lists in R (Practice)

Lecture 9: Lists in R (Exercise)

Lecture 10: Lists in R (Solution)

Lecture 11: Functions in R (Theory)

Lecture 12: Functions in R (Practice)

Lecture 13: Functions in R(Exercise)

Lecture 14: Functions in R (Solution)

Lecture 15: Matrix in R (Theory)

Lecture 16: Matrix in R (Practice)

Lecture 17: Matrix in R (Exercise)

Lecture 18: Matrix in R (Solution)

Lecture 19: Arrays in R (Theory)

Lecture 20: Arrays in R (Practice)

Lecture 21: Arrays in R (Exercise)

Lecture 22: Arrays in R (Solution)

Lecture 23: Data frames in R (Theory)

Lecture 24: Data frames in R (Practice)

Lecture 25: Data frames in R (Exercise)

Lecture 26: Data frames in R (Solution)

Lecture 27: Factors in R (Theory)

Lecture 28: Factors in R (Practice)

Lecture 29: Factors in R (Exercise)

Lecture 30: Factors in R (Solution)

Chapter 5: Jupyter Notebook Crash Course

Lecture 1: What is Jupyter Notebook

Lecture 2: Installing Anaconda

Lecture 3: Opening Jupyter Notebook

Lecture 4: Edit-Command-Mode

Lecture 5: Autocomplete

Lecture 6: Menus Overview

Lecture 7: What is Markdown

Instructors

Fahad Masood Reda
Data Science & MIS Mentor | Founder of TheMIS & DataArena

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 11 votes

5 stars: 30 votes

Frequently Asked Questions

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