Learn how to manipulate and analyze data.
This path covers everything you need to learn to work as a data analyst using R.
You'll learn the fundamentals of R syntax, dig into data analysis and data viz using popular tidyverse packages, query databases with SQL, and study statistics, among other things!
Each path is designed so that there are no prerequisites and no prior experience required. Everything you need to learn to work as a data analyst, you'll learn on this path!
As you learn, you'll apply each concept immediately by writing code right in your browser that's automatically checked by our system to give you near-instant feedback on your progress.
We think the best way to learn is to learn by doing, so you'll be challenged every step of the way to really apply the concepts you're learning, and you'll build a variety of projects using real-world data to solve real data analysis problems.
By the end of this path, you'll have the skills you need to work as a data analyst, and you'll be comfortable with things like:
Learn Data Analysis with R
Introduction to Data Analysis in R
Learn the basics of R, a popular programming language for data analysis.
Data Structures in R
Learn about vectors, matrices, lists, dataframes, and more in R.
Control Flow, Iteration, and Functions in R
Enhance your R programming skills with if statements, for loops, and much more.
Specialized Data Processing in R: Strings and Dates
Learn to work with specialized data types like text data, times, and dates in R.
Data Visualization in R
Learn to use the ggplot2 package for exploratory data visualization in R.
Data Cleaning in R
Learn to perform common data cleaning tasks.
Storytelling Through Data Visualization in R
Learn how to communicate insights and tell stories using data visualization.
Data Cleaning in R: Advanced
Learn advanced techniques for cleaning data in R.
Learn the basics of working with SQL databases.
SQL Intermediate in R
Learn to work with multi-table databases.
APIs and Web Scraping in R
Learn how to acquire data from APIs and the web.
Statistics Fundamentals for R Users
Learn the basics of statistics.
Statistics Intermediate in R: Averages and Variability
Learn some intermediate statistic techniques such as calculating z-scores.
Probability Fundamentals for R Users
Learn the fundamentals of probability for data science.
Hypothesis Testing in R
Learn the fundamentals of hypothesis testing using R
Conditional Probability in R
Learn about conditional probability and Naive Bayes in R
Linear Modeling in R
Learn linear regression modeling in R.
Introduction to Machine Learning
Learn the fundamentals of machine learning with R and the caret library.
Command Line Fundamentals for R Users
Learn about the command line and how it can be used in the data science workflow.
Git and Version Control for R Users
Learn how to use Git for version control in the data science workflow.