Step Into SQL with Jupyter Notebooks

Overview

This course introduces you to the essential tools and techniques of modern data analysis. Begin by establishing a professional SQL environment using Jupyter Notebooks where you'll learn fundamental SQL syntax, construct your first queries, and apply filtering with WHERE clauses. As you progress, you'll integrate powerful version control practices using Git and GitHub—mastering repository management, commit strategies, and branching techniques critical for collaborative data work. By completing this course, you'll possess both the technical SQL skills to extract insights from data and the professional workflow capabilities that distinguish casual analysts from industry professionals. Upon completion, you'll be able to: • Configure a professional SQL environment using Jupyter Notebooks and write effective queries with SELECT statements and WHERE clauses • Implement Git version control for SQL projects, including repository setup, commits, and branching strategies • Collaborate on data science projects through GitHub, maintaining code integrity while enabling team contributions • Apply industry best practices for SQL code versioning, documentation, and workflow management in professional data environments

Syllabus

Introduction to SQL and Environment Setup

In this introductory module, you'll jumpstart your journey into the world of SQL and data science. You'll set up a professional-grade development environment using Jupyter Notebooks, master basic SQL syntax, and craft your first SELECT statements with WHERE clauses.

Version Control Basics with Git

This module equips you with essential version control skills for data science, covering SQL environment setup and basic querying before introducing Git integration into your workflow. You'll learn best practices for versioning SQL scripts and master fundamental Git and GitHub operations—including repository management, commits, and branching—enabling you to collaborate effectively while maintaining code integrity across data projects.