Welcome to my learning journey through the SQL for Data Science course offered by Codebasics, taught by Dhaval Patel and designed by Hemanand Vadivel.
This course is specially designed for:
- 👩💻 Beginners in Data Analysis
- 📈 Aspiring Data Analysts / Data Scientists
- 💼 Professionals wanting to strengthen SQL for real-world use cases
This course uses real-world business problems and datasets to teach core SQL concepts. Here's a quick overview of what I covered:
| 📌 Chapter | 🔍 Topics Covered |
|---|---|
| 1. SQL Basics | SELECT, Filtering, WHERE clause |
| 2. Operators | AND, OR, BETWEEN, IN, LIKE, Wildcards |
| 3. Aggregation | COUNT, SUM, AVG, MIN, MAX, GROUP BY, HAVING |
| 4. Subqueries & CTEs | Subqueries, Co-related Subqueries, CTE, ANY & ALL |
| 5. SQL Joins | INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN |
| 6. Case Study: Movie Dataset | Advanced filtering, joins, nested queries |
| 7. Window Functions | RANK(), DENSE_RANK(), ROW_NUMBER() |
| 8. Case Study: HR Dataset | Real-life queries on employees, departments |
| 9. Final Quiz | Application of all learned skills in one go |
- Database: MySQL 8.0
- IDE: MySQL Workbench
- Datasets: MovieDB, HR, Financials, E-commerce (provided by Codebasics)
- 🎬 Fetch actors with the highest number of movies
- 💼 Find employees with above-average salaries per department
- 💰 Calculate profit % of movies and filter based on rating
- 🧓 Find actors aged between 70 and 85 using
CURDATE()logic - 🏆 Use CTEs to simplify nested logic and subqueries
✅ All queries were written, tested, and debugged using real datasets inside MySQL Workbench.
- Mastered writing complex SQL queries
- Understood business logic behind queries
- Learned how to clean, join, filter, and rank data
- Got hands-on with real datasets and case studies
- Learned how SQL powers data analytics and dashboards
A heartfelt thanks to:
- Dhaval Patel Sir – for his crystal-clear explanations and real-world insights
- Hemanand Sir – for designing such a thoughtful and practical course curriculum
Their efforts made this journey not just educational but also fun and exciting.
✅ Check
/screenshotsfolder (if this is a GitHub repo) to view:
- My subquery and CTE solutions
- Movie dataset profit filtering
- Age-based queries with CURDATE
- Window function usage
As a BCA student and aspiring Data Analyst, this course gave me the practical SQL knowledge required in the real-world data industry.
Now I feel confident in:
- Cracking SQL Interviews
- Creating Data-Driven Dashboards
- Working with Analytical Teams
If you're also learning SQL or Data Analytics, feel free to connect with me:
- 🧑💻 GitHub
- 📧 your.email@example.com
“Data is the new oil — and SQL is the pipeline.” 🚀