Databases and SQL for Data Science with Python

This repository contains exercises and projects for learning SQL (Structured Query Language), an essential skill for data professionals such as Data Scientists, Data Analysts, and Data Engineers. These exercises cover fundamental to advanced SQL concepts through hands-on practice.

Course Overview

SQL is widely used for extracting and manipulating data stored in databases. This repository provides a structured approach to mastering SQL, covering topics such as:

• Writing foundational SQL statements: SELECT, INSERT, UPDATE, DELETE.
• Filtering and manipulating result sets with WHERE, COUNT, DISTINCT, and LIMIT.
• Understanding DML (Data Manipulation Language) and DDL (Data Definition Language).
• Creating, modifying, and deleting tables using CREATE, ALTER, and DROP.
• Applying string patterns, ranges, ORDER BY, GROUP BY, and built-in functions.
• Constructing subqueries and retrieving data from multiple tables.
• Working with SQL and Python in Jupyter Notebooks.
• Exploring advanced topics: Stored Procedures, Views, ACID Transactions, and JOINs.

Credits

This course and its exercises are part of the Databases and SQL for Data Science with Python curriculum developed by IBM Skills Network.