Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2
InstructorKirill Eremenko
Technical concepts are framed through specific industry-style briefs, including financial data cleaning and weather pattern analysis.
Instruction covers the Apply family, including lapply(), sapply(), and the ability to nest these functions.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
The RStudio console displays the head of a financial dataset containing company details like industry, revenue, expenses, and profit growth.
The RStudio environment demonstrates deriving utilization columns and converting timestamps to POSIXct format, with the console displaying the resulting data table.
The RStudio interface displays code using lapply and sapply functions to process weather data, with the console showing a resulting table of normalized values by city and month.
The RStudio environment displays ggplot2 code generating a boxplot visualization that compares growth metrics across various industries.
Learner signals suggest the content may not reach true advanced levels, specifically regarding custom function architecture or code structuring.
The curriculum lacks extensive coverage of the modern tidyverse ecosystem.
The course requires basic R knowledge, but the 'advanced' label creates uncertainty regarding its actual difficulty level.