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.
Step Into SQL with Jupyter Notebooks
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Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
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Recently updated!
July 2025
Assessments
1 assignment
Taught in English
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There are 2 modules in this course
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.
What's included
7 readings1 assignment1 programming assignment2 ungraded labs1 plugin
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.
What's included
4 readings1 ungraded lab1 plugin
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