SQL for Data Science

SQL for Data Science

This handbook covers SQL from the ground up. You set up PostgreSQL, create tables and write queries to select, filter and sort data. You then summarize it with GROUP BY, combine tables with joins and clean messy data. The later modules cover subqueries, CTEs, window functions and query performance. The handbook ends with using SQL alongside Python and pandas, a mini project and common interview questions.

SQL for Data Science

SQL for Data Science matters for the following reasons: - Data is often stored in databases, and SQL is how you read it. - You can filter, join and clean data before analysis begins. - Window functions and CTEs handle advanced analysis inside the database. - Indexes keep queries fast on large tables. - Query results move easily into Python and pandas.

SQL for Data Science

This handbook is useful for the following learners: - Students and beginners who want to start with SQL for data science. - Data analysts who want to practice joins, grouping and window functions. - Python and pandas users who want to pull data from a database. - Working professionals who need to use SQL to read company data. - Anyone preparing for SQL questions in a data role interview.

Prerequisites

This course is suitable for:

• No prior SQL experience is needed
• A computer where you can install PostgreSQL, which is free
• A basic understanding of rows and columns, like in an Excel sheet
• Willingness to run the examples yourself as you read