New Course: SQL Intermediate for R Users

June 27, 2019

SQL may be a decades-old language, but SQL skills are as relevant as they’ve ever been in the world of data science. In fact, SQL is arguably the most important language in data science — more people working in data use it than use Python or R, according to StackOverflow’s 2018 survey.

We offer a number of SQL courses geared towards Python programmers, but we know that R users need to integrate SQL into their workflows, too! As we expand our Data Analyst in R path, we’ve already launched a new SQL Fundamentals for R Users course, and now we’re launching the sequel: SQL Intermediate for R Users

This course is part of our Data Analyst in R path. The first four courses of this path are free; however, this course requires at least a Basic subscription.

What You’ll Learn in SQL Intermediate for R Users

In this course, you’ll build on the skills you’ve already developed in the SQL Fundamentals for R Users course to use SQL and R for more complex tasks. Along the way, you’ll learn to use resources like RSQLite, DBI, and the tidyverse in modern, real-world SQL and R data workflows.

Like all of our courses, this course is completed interactively, and you'll be learning and writing your code (both SQL and R) right in your browser window, like this:


The Dataquest platform in a nutshell.

You’ll start by learning about SQL joins, and learn to use joins to query data across multiple tables. Then you’ll go deeper, learning to join data from more complex databases and write more complex queries to get exactly the data you need.

Then, you’ll work on some SQL best practices for real-world SQL work. We’ll cover techniques for organizing your queries and keeping them easy to read, and then walk you through a real-world data analysis workflow using SQL and R to answer business questions.

Finally, you’ll learn about the SQLite shell and use it to work with, create, and normalize your own databases. Then you’ll synthesize all of your new SQL skills in a guided project designing, creating, and populating a normalized SQL database from scratch.

Why You Need to Learn SQL for R

The answer to this question is pretty straightforward: SQL databases are everywhere. If you’re planning to use your R programming skills to work with data in pretty much any role, you’re going to run into situations where SQL skills are required. That’s why you’ll see SQL on the skills list for just about every job listing that involves working with data.

And although SQL doesn’t have the glamour of trendy data science tasks like building machine learning models, the reality is that in the vast majority of data jobs, you’ll be spending a lot more of your time acquiring, preparing, and cleaning data than you spend on building the model. SQL may be old, but it’s still a necessary skill for those kinds of data acquisition and manipulation tasks.

You don’t have to take our word for it! Check out some job listings for yourself. Even data analyst jobs, which are often considered entry-level, require SQL skills. It’s the first technical skill listed for this Data Analyst job at Google, for example. Ditto this job at Dropbox. Same with this job at Reddit. And this job at Twitch. Almost any data job you can find is going to list SQL as a requirement, because SQL databases are so ubiquitous.

If you need to improve your SQL skills, there’s no time like the present! Dive in and take your SQL skills to the next level:


announcements, course launches, intermediate, r, rstats, SQL

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