In this path, you’ll learn the fundamentals of R and build upon them with more advanced skills. You’ll learn how to use RStudio, applications and tools, tidyverse, DataFrames, tibbles, operators, expressions, and much more — as well as data visualization, graphs, plots, and charts.
Best of all, you’ll learn by doing — you’ll write code and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.
- Programming with R to perform complex statistical analysis of large datasets
- Performing SQL queries and web-scraping to explore and extract data from databases and websites
- Performing efficient data analysis from start to finish
- Building insightful data visualizations to tell stories
Part 1: Introduction to R [4 courses]
Part 3: Data Cleaning in R [2 courses]
Part 4: Working with Data Sources Using SQL [6 courses]
Part 6: Probability and Statistics [5 courses]
Part 7: Predictive Modeling and Machine Learning in R [2 courses]
Part 8: Shiny Applications in R [1 course]
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We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
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Projects in this path
Project: Install RStudio
Learn how to install and use RStudio, a free and open-source development environment for R.
Guided Project: Investigating COVID-19 Virus Trends
Learn to combine the skills you learned in this course to perform practical data analysis.
Guided Project: Creating An Efficient Data Analysis Workflow
Apply control flow, loops and functions to create a reusable data workflow.
Guided Project: Creating An Efficient Data Analysis Workflow, Part 2
Employ even more programming techniques to create a reusable data workflow.
Guided Project: Analyzing Forest Fire Data
Use data visualization techniques to explore data on forest fires.