R Programming: Advanced Analytics In R For Data Science
Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2
4.65 (9067 reviews)
62 618
students
6 hours
content
Feb 2025
last update
$109.99
regular price
What you will 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
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Our Verdict
Boasting a solid 4.65 rating and 62k+ subscribers, this advanced R programming course by Kirill Eremenko targets data preparation and the apply() family of functions, providing valuable insights for enthusiasts and practitioners alike. While some users find the content more basic than advanced or the price too high, overall, it's a laudable e-learning experience that bridges theory and real-life applications, effectively equipping students with essential skills for data analytics with R.
What We Liked
- Covers advanced topics like data preparation, apply() family of functions and lists.
- Content is useful for both beginners and those looking to deepen their knowledge in R.
- Kirill's teaching style effectively blends theory with real-world applications.
- Well-structured course with clear and easily explained tutorials.
Potential Drawbacks
- Course price is considered high for the number of sections and tutorials.
- Lacks exercises at the end of each section to practice newly learned concepts.
- Some users find the content more basic than advanced, possibly better suited for beginners.
- Additional focus on script/code organization techniques could be beneficial.
Related Topics
860148
udemy ID
26/05/2016
course created date
06/11/2019
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