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 (9076 reviews)

Udemy

platform

English

language

Data Science

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

Course Gallery

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Comidoc Review

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.