R Programming: Advanced Analytics In R For Data Science-telecourses

 Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2

What you'll learn

·         Perform Data Preparation in R

·         Identify missing records in dataframes

·         Locate missing data in your dataframes

·         Apply the Median Imputation method to replace missing records

·         Apply the Factual Analysis method to replace missing records

·         Understand how to use the which() function

·         Know how to reset the dataframe index

·         Work with the gsub() and sub() functions for replacing strings

·         Explain why NA is a third type of logical constant

·         Deal with date-times in R

·         Convert date-times into POSIXct time format

·         Create, use, append, modify, rename, access and subset Lists in R

·         Understand when to use [] and when to use [[]] or the $ sign when working with Lists

·         Create a timeseries plot in R

·         Understand how the Apply family of functions works

·         Recreate an apply statement with a for() loop

·         Use apply() when working with matrices

·         Use lapply() and sapply() when working with lists and vectors

·         Add your own functions into apply statements

·         Nest apply(), lapply() and sapply() functions within each other

·         Use the which.max() and which.min() functions

 

Requirements

·         Basic knowledge of R

·         Knowledge of the GGPlot2 package is recommended

·         Knowledge of dataframes

·         Knowledge of vectors and vectorized operations

 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.

Who this course is for:

·         Anybody who has basic R knowledge and would like to take their skills to the next level

·         Anybody who has already completed the R Programming A-Z course

·         This course is NOT for complete beginners in R

 

https://www.udemy.com/course/r-analytics/