SQL is an essential skill for all data professionals, and mastering it requires continued learning. Several free SQL courses can aid in learning and becoming proficient in SQL for data science. They range from the basics of relational databases and SQL to NoSQL databases.
The first available course, ‘SQL Tutorial – Full Database Course for Beginners,’ provides an introduction to SQL and database management systems basics. It covers CRUD operations, Schema design, Aggregation, Nested queries, Joins and Unions, Functions, Triggers, and ER diagrams.
Another top course is the ‘Mode SQL Tutorial’, which is a comprehensive tutorial segmented into four modules: Basic SQL, Intermediate SQL, Advanced SQL, and SQL analytics training. Learners get to practice SELECT, LIMIT, WHERE clause, and much more in the Basic SQL module. Intermediate SQL covers aggregate functions, Group by and having, Distinct, and different types of joins. In the Advanced SQL module, topics like data types: dates and strings, SQL string functions, window functions, subqueries, and performance tuning, are covered.
Coursera also offers the ‘Learn SQL Basics for Data Science Specialization,’ allowing for a broad study of SQL used in data science careers. It consists of four courses: SQL for Data Science, Data wrangling analysis, AB testing with SQL, Distributed Computing with Spark SQL, and SQL for Data Science Capstone Project. To receive a verified certificate from Coursera, a Coursera Plus subscription is required.
The course titled ‘NoSQL vs. SQL- Which Type of Database Should You Use?’ provides the characteristics of SQL and NoSQL databases, the need for NoSQL databases, the pros and cons of each database type, and when to use RDBMS vs. NoSQL databases.
Lastly, the ‘NoSQL Database Tutorial – Full Course for Beginners’ explains why NoSQL databases should be used, different types of NoSQL databases, and working on projects.
All these SQL courses are available for free. Individuals with little knowledge of SQL may opt for the SQL for data science specialization. These courses can open up a wealth of knowledge in the world of data science.
