Data Scientist with R

Learn how to use R for data science, from data manipulation to machine learning, and gain the career-building R skills you need to succeed as a data scientist. As you progress through the courses in this track, you’ll explore how learning data science with R can help you to import, clean, manipulate, and visualize data. R is a versatile language for any aspiring data professional or researcher, and by learning the integral skills, you’ll develop a solid foundation for your data science journey. Through interactive exercises, you’ll get hands-on with some of the most popular R packages, including tidyverse packages like ggplot2, dplyr, and readr. You’ll work with real-world datasets as you write your own functions and learn foundational statistical and machine learning techniques. Start this track, grow your R programming and data science skills, and begin your journey to becoming a confident data scientist.

R88 hours22 Courses

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Introduction to R

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

4 hours

Intermediate R

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

6 hours

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

4 hours

Data Manipulation with dplyr

Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.

4 hours

Joining Data with dplyr

Learn to combine data across multiple tables to answer more complex questions with dplyr.

4 hours

Introduction to Statistics in R

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

4 hours

Introduction to Data Visualization with ggplot2

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

4 hours

Intermediate Data Visualization with ggplot2

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

4 hours

Data Manipulation with R

Data Communication Concepts

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

3 hours

Introduction to Importing Data in R

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

3 hours

Cleaning Data in R

Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.

4 hours

Working with Dates and Times in R

Learn the essentials of parsing, manipulating and computing with dates and times in R.

4 hours

Importing & Cleaning Data with R

Introduction to Writing Functions in R

Take your R skills up a notch by learning to write efficient, reusable functions.

4 hours

R Programming

Exploratory Data Analysis in R

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

4 hours

Introduction to Regression in R

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

4 hours

Intermediate Regression in R

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hours

Sampling in R

Master sampling to get more accurate statistics with less data.

4 hours

Hypothesis Testing in R

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

4 hours

Experimental Design in R

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

4 hours

Statistics Fundamentals with R

Supervised Learning in R: Classification

In this course you will learn the basics of machine learning for classification.

4 hours

Supervised Learning in R: Regression

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hours

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hours

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Join over .css-1osvizq-TrackShowPage{color:#03ef62;}11,710,000 learners and start Data Scientist with R today!

Create Your Free Account

Join over 11,710,000 learners and start Data Scientist with R today!