R Programming: Advanced Analytics In R For Data Science - Online Course Download
What you'll learn :
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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 :
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Basic knowledge of R Knowledge of the GGPlot2 package is recommended Knowledge of dataframes Knowledge of vectors and vectorized operations
Description :
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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 :
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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
Course Size Details :
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6 hours on-demand video 5 articles Full lifetime access Access on mobile and TV Certificate of completion
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