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 don't 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 don't 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 don't 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 don't 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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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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