Layers of AI

𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 𝗕𝘆 𝗜𝗜𝗧 𝗥𝗼𝗼𝗿𝗸𝗲𝗲 😍

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SQL is one of the core languages used in data science, powering everything from quick data retrieval to complex deep dive analysis. Whether you're a seasoned data scientist or just starting out, mastering SQL can boost your ability to analyze data, create robust pipelines, and deliver actionable insights.

Let’s dive into a comprehensive guide on SQL for Data Science!

I have broken it down into three key sections to help you:

𝟭. 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
Get a handle on the essentials -> SELECT statements, filtering, aggregations, joins, window functions, and more.

𝟮. 𝗦𝗤𝗟 𝗶𝗻 𝗗𝗮𝘆-𝘁𝗼-𝗗𝗮𝘆 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲:
See how SQL fits into the daily data science workflow. From quick data queries and deep-dive analysis to building pipelines and dashboards, SQL is really useful for data scientists, especially for product data scientists.

𝟯. 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗦𝗤𝗟 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀:
Learn what interviewers look for in terms of technical skills, design and engineering expertise, communication abilities, and the importance of speed and accuracy.

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Hope it helps :)

#sql

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It includes full-fledged lectures at a top-university level, available for free.

What's in the course

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30-day Roadmap plan for SQL covers beginner, intermediate, and advanced topics 👇

Week 1: Beginner Level

Day 1-3: Introduction and Setup
1. Day 1: Introduction to SQL, its importance, and various database systems.
2. Day 2: Installing a SQL database (e.g., MySQL, PostgreSQL).
3. Day 3: Setting up a sample database and practicing basic commands.

Day 4-7: Basic SQL Queries
4. Day 4: SELECT statement, retrieving data from a single table.
5. Day 5: WHERE clause and filtering data.
6. Day 6: Sorting data with ORDER BY.
7. Day 7: Aggregating data with GROUP BY and using aggregate functions (COUNT, SUM, AVG).

Week 2-3: Intermediate Level

Day 8-14: Working with Multiple Tables
8. Day 8: Introduction to JOIN operations.
9. Day 9: INNER JOIN and LEFT JOIN.
10. Day 10: RIGHT JOIN and FULL JOIN.
11. Day 11: Subqueries and correlated subqueries.
12. Day 12: Creating and modifying tables with CREATE, ALTER, and DROP.
13. Day 13: INSERT, UPDATE, and DELETE statements.
14. Day 14: Understanding indexes and optimizing queries.

Day 15-21: Data Manipulation
15. Day 15: CASE statements for conditional logic.
16. Day 16: Using UNION and UNION ALL.
17. Day 17: Data type conversions (CAST and CONVERT).
18. Day 18: Working with date and time functions.
19. Day 19: String manipulation functions.
20. Day 20: Error handling with TRY...CATCH.
21. Day 21: Practice complex queries and data manipulation tasks.

Week 4: Advanced Level

Day 22-28: Advanced Topics
22. Day 22: Working with Views.
23. Day 23: Stored Procedures and Functions.
24. Day 24: Triggers and transactions.
25. Day 25: Windows Function

Day 26-30: Real-World Projects
26. Day 26: SQL Project-1
27. Day 27: SQL Project-2
28. Day 28: SQL Project-3
29. Day 29: Practice questions set
30. Day 30: Final review and practice, explore advanced topics in depth, or work on a personal project.

Like for more ❤️

Free Resources to learn SQL: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v/1394