I would work through Learning SQL first, then read SQL for Data Analysis (both by O’Reilly). The former one teaches the fundamentals using MySQL, while the latter goes more into analysis using Postgres. More on reddit.com

Thanks a lot! My SQL knowledge is scattered so I've been meaning to do a structured course. More on reddit.com

For beginners, The SQL Murder Mystery is a fun way to start your learning:
https://mystery.knightlab.com/

I have also found the training at Maven Analytics (MavenAnalytics.io) to be quite decent. They teach using scenarios that would likely be used in real world settings. As an aside, last I checked, the training modules forward you to their Udemy.com classes. But they offer a monthly subscription so that you can access several courses at once.

Another option is to find a charity in need of some data analysis (preferrably one that has an installation of a SQL engine already). Offer your services for free with the understanding that you are learning and it may take longer than people with experience. If you get stuck, simply seek out help on forums, etc. Volunteering does count as experience which you can put on your resume. Besides, it is always a great idea to help people in need.

Hope this helps!

More on reddit.com

SQL Basics W3's SQL Tutorials SQL Server Tutorial SQL Zoo Tutorial Stack Overflow Query SQL Server Oracle Live SQL server [Oracle's Dev Gym for SQL] ( https://devgym.oracle.com/pls/apex/f?p=10001:20011::::20011 ::) Oracle Tutorial Coursera MySQL SQL Exercises W3's SQL Exercises The SQL Mystery Solving Exercise Selectstar SQL Exercises Leetcode's SQL Exercises Hackerrank's SQL Exercises PG Exercises in PostGreSQL Interview Query Exercises Stratascratch Exercises SQL Educational Videos and Programs SQL for Data Scientists FreeCodeCamp 4 hour SQL tutorial FreeCodeCamp Relational Database Courses Database Security Cornell University, Introduction to Database 25 hours Database Systems Research Group Advanced SQL series Brent Ozar Unlimited SQL The SQL programming language was developed in the 1970s by IBM researchers Raymond Boyce and Donald Chamberlin. The programming language, known then as SEQUEL, was created following Edgar Frank Codd's paper, “A Relational Model of Data for Large Shared Data Banks,” in 1970. IBM invented Relational Databases and SQL. IBM SQL Certificate Programs (IBM Programs range from hours to months to almost a year to complete) IBM Data Analyst Career Guide IBM Data Scientist Career Guide IBM Beginner Certificate Programs IBM Intro to Relational Databases IBM Intro to Data Analytics IBM Intro to Data Science IBM Data Engineering Foundations program IBM Data Analyst program IBM Data Science program IBM Applied Data Science program IBM Data Engineering program IBM Data Warehouse Engineering program IBM Data Science with Python & SQL specialization program IBM Data Analysis Visualization program IBM BI Foundations with SQL and more program IBM Data Analysis with R IBM Intro to R programming IBM Applied Data Science with R specialization program IBM SQL for Data Science with R program IBM Developing Applications with SQL and more program IBM Data Analytics with Excel and R program IBM Intermediate Certificate Programs IBM Intermediate Data Analyst Capstone IBM Intermediate Applied Data Science Capstone IBM's Sole Advanced Certificate Program IBM Advanced Data Science program College-Level Notable SQL Programs Duke University's Python / SQL course. UC Davis Learn SQL Cloudera Big Data SQL CS50 All this. This should keep you busy and ranges from training, to education, to practice and all in between down to security. Then there's the gamut of Python you might want to know atop this. So Dr. Chuck's aka Charles Severance Python for Everybody. Python For Everybody Python for Data Analysis: Pandas & NumPy Also, one more thing... OSSU's Data Science Degree equivalent program Open Source Society List of classes to take to learn advanced data science. OSSU's Computer Science Degree equivalent program And Open Source Society's list of classes in computer science. More on reddit.com