R Programming A-Z: R For Data Science With Real Exercises!
4.8 /5- Offered byUDEMY
R Programming A-Z: R For Data Science With Real Exercises! at UDEMY Overview
Duration | 11 hours |
Total fee | ₹699 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
R Programming A-Z: R For Data Science With Real Exercises! at UDEMY Highlights
- Compatible on Mobile and TV
- Earn a Cerificate on successful completion
- Get Full Lifetime Access
R Programming A-Z: R For Data Science With Real Exercises! at UDEMY Course details
- 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
- 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
- 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
R Programming A-Z: R For Data Science With Real Exercises! at UDEMY Curriculum
Hit The Ground Running
Welcome to the R Programming Course!
Updates on Udemy Reviews
Installing R and R Studio (MAC & Windows)
BONUS: Learning Paths
Exercise - Get Excited!
BONUS: Using R in The Real World
Some Additional Resources!!
Core Programming Principles
Welcome to this section. This is what you will learn!
Types of variables
Using Variables
Logical Variables and Operators
The "While" Loop
Using the console
The "For" Loop
The "If" statement
Section Recap
HOMEWORK: Law of Large Numbers
Fundamentals Of R
Welcome to this section. This is what you will learn!
What is a Vector?
Let's create some vectors
Using the [] brackets
Vectorized operations
The power of vectorized operations
Functions in R
Packages in R
Section Recap
HOMEWORK: Financial Statement Analysis
Matrices
Welcome to this section. This is what you will learn!
Project Brief: Basketball Trends
Matrices
Building Your First Matrix
Naming Dimensions
Colnames() and Rownames()
Matrix Operations
Visualizing With Matplot()
Subsetting
Visualizing Subsets
Creating Your First Function
Basketball Insights
Section Recap
HOMEWORK: Basketball Free Throws
Data Frames
Welcome to this section. This is what you will learn!
Project Brief: Demographic Analysis
Importing data into R
Exploring your dataset
Using the $ sign
Basic operations with a Data Frame
Filtering a Data Frame
Introduction to qplot
Visualizing With Qplot: Part I
Building Dataframes
Merging Data Frames
Visualizing With Qplot: Part II
Section Recap
HOMEWORK: World Trends
Advanced Visualization With GGPlot2
Welcome to this section. This is what you will learn!
Project Brief: Movie Ratings
Grammar Of Graphics - GGPlot2
What is a Factor?
Aesthetics
Plotting With Layers
Overriding Aesthetics
Mapping vs Setting
Histograms and Density Charts
Starting Layer Tips
Statistical Transformations
Using Facets
Coordinates
Perfecting By Adding Themes
Section Recap
HOMEWORK: Movie Domestic % Gross
Homework Solutions
Homework Solution Section 2: Law Of Large Numbers
Homework Solution Section 3: Financial Statement Analysis
Homework Solution Section 4: Basketball Free Throws
Homework Solution Section 5: World Trends
Homework Solution Section 6: Movie Domestic % Gross (Part 1)
Homework Solution Section 6: Movie Domestic % Gross (Part 2)
THANK YOU bonus video
Bonus Tutorials
BoxPlots
**YOUR SPECIAL BONUS**
Bonus Lectures
Conclusion
Course Overview And Roadmap Download
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