Intermediate SQL

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

Start Course for Free
4 Hours15 Videos55 Exercises93,844 Learners
4700 XP

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).

Loved by learners at thousands of companies


Course Description

So you've learned how to aggregate and join data from tables in your database—now what? How do you manipulate, transform, and make the most sense of your data? This intermediate-level course will teach you several key functions necessary to wrangle, filter, and categorize information in a relational database, expand your SQL toolkit, and answer complex questions. You will learn the robust use of CASE statements, subqueries, and window functions—all while discovering some interesting facts about soccer using the European Soccer Database.

  1. 1

    We'll take the CASE

    Free

    In this chapter, you will learn how to use the CASE WHEN statement to create categorical variables, aggregate data into a single column with multiple filtering conditions, and calculate counts and percentages.

    Play Chapter Now
    We'll take the CASE
    50 xp
    Basic CASE statements
    100 xp
    CASE statements comparing column values
    100 xp
    CASE statements comparing two column values part 2
    100 xp
    In CASE things get more complex
    50 xp
    In CASE of rivalry
    100 xp
    Filtering your CASE statement
    100 xp
    CASE WHEN with aggregate functions
    50 xp
    COUNT using CASE WHEN
    100 xp
    COUNT and CASE WHEN with multiple conditions
    100 xp
    Calculating percent with CASE and AVG
    100 xp
  2. 3

    Correlated Queries, Nested Queries, and Common Table Expressions

    In this chapter, you will learn how to use nested and correlated subqueries to extract more complex data from a relational database. You will also learn about common table expressions and how to best construct queries using multiple common table expressions.

    Play Chapter Now

In the following tracks

SQL Fundamentals

Collaborators

Sumedh PanchadharHillary Green-Lerman

Prerequisites

Joining Data in SQL
Mona Khalil Headshot

Mona Khalil

Data Scientist, Greenhouse Software

As a senior data scientist at Greenhouse, Mona answers questions related to how the hiring process can be improved to find better candidates quicker and reduce bias in the hiring process. They previously worked in education, marketing, and local government. They also co-host Bad Methods, a podcast that brings a fun and interesting lens to critically evaluating science. You can find them on twitter at mona_kay_.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA