R Programming for Statistics and Data Science

R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGplot2 in R

4.49 (5541 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Learn the fundamentals of programming in R

Work with R’s conditional statements, functions, and loops

Build your own functions in R

Get your data in and out of R

Learn the core tools for data science with R

Manipulate data with the Tidyverse ecosystem of packages

Systematically explore data in R

The grammar of graphics and the ggplot2 package

Visualise data: plot different types of data & draw insights

Transform data: best practices of when and how

Index, slice, and subset data

Learn the fundamentals of statistics and apply them in practice

Hypothesis testing in R

Understand and carry out regression analysis in R

Work with dummy variables

Learn to make decisions that are supported by the data!

Have fun by taking apart Star Wars and Pokemon data, as well some more serious data sets

Course Gallery

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Comidoc Review

Our Verdict

The R Programming for Statistics and Data Science course stands out with its unique blend of programming fundamentals and statistical analysis, presented in a well-organized package by an experienced instructor. While some statistics concepts might be rushed or insufficiently explained, students have access to valuable hands-on exercises that facilitate learning. However, this course could benefit from enhanced documentation for code examples and better synchronization between exercise releases and course progression.

What We Liked

Comprehensive coverage of R programming and statistical analysis
Well-organized course material, clear instructions and concise explanations
Hands-on exercises with practical examples and helpful tips
Expert instructor with strong background in statistics

Potential Drawbacks

Some statistics concepts could be explained more thoroughly
Occasional discrepancies between exercise availability and course progression
Lack of documentation for the course code examples