Module 1Module 1 – Welcome To The Course
Unit 1Welcome to the Advanced R Programming Course!
Module 2Module 2 – Data Preparation
Unit 1Welcome to this section. This is what you will learn!
Unit 2Project Brief: Financial Review
Unit 3Import Data into R
Unit 4What are Factors (Refresher)
Unit 5The Factor Variable Trap
Unit 6FVT Example
Unit 7gsub() and sub()
Unit 8Dealing with Missing Data
Unit 9What is an NA?
Unit 10An Elegant Way To Locate Missing Data
Unit 11Data Filters: which() for Non-Missing Data
Unit 12Data Filters: is.na() for Missing Data
Unit 13Removing records with missing data
Unit 14Reseting the dataframe index
Unit 15Replacing Missing Data: Factual Analysis Method
Unit 16Replacing Missing Data: Median Imputation Method (Part 1)
Unit 17Replacing Missing Data: Median Imputation Method (Part 2)
Unit 18Replacing Missing Data: Median Imputation Method (Part 3)
Unit 19Replacing Missing Data: Deriving Values Method
Unit 20Visualizing results
Unit 21Section Recap
Unit 22Quiz 1 – Data Preparation
Module 3Module 3 – Lists in R
Unit 1Welcome to this section. This is what you will learn!
Unit 2Project Brief: Machine Utilization
Unit 3Import Data Into R
Unit 4Handling Date-Times in R
Unit 5What is a List?
Unit 6Naming components of a list
Unit 7Extracting components lists: [] vs [[]] vs $
Unit 8Adding and deleting components
Unit 9Subsetting a list
Unit 10Creating A Timeseries Plot
Unit 11Section Recap
Unit 12Quiz 2 – Lists in R
Module 4Module 4 – “Apply” Family Of Functions
Unit 1Welcome to this section. This is what you will learn!
Unit 2Project Brief: Weather Patterns
Unit 3Import Data into R
Unit 4What is the Apply family?
Unit 5Using apply()
Unit 6Recreating the apply function with loops (advanced topic)
Unit 7Using lapply()
Unit 8Combining lapply() with []
Unit 9Adding your own functions
Unit 10Using sapply()
Unit 11Nesting apply() functions
Unit 12which.max() and which.min() (advanced topic)
Unit 13Section Recap
Unit 14Quiz 3 – “Apply” Family of Functions
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Advanced R Programming

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Course Description

Ready to take your R Programming skills to the next level?

Want to truly become proficient at Data Science and Analytics with R?

This course is for you!

Professional R Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for Analytics of the REAL WORLD.

In this course you will learn:

  • How to prepare data for analysis in R
  • How to perform the median imputation method in R
  • How to work with date-times in R
  • What Lists are and how to use them
  • What the Apply family of functions is
  • How to use apply(), lapply() and sapply() instead of loops
  • How to nest your own functions within apply-type functions
  • How to nest apply(), lapply() and sapply() functions within each other
  • And much, much more!

The more you learn the better you will get. After every module you will already have a strong set of skills to take with you into your Data Science career.