SQL in 30 Days
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: Security and user privileges.
26. Day 26: Performance tuning and query optimization.
27. Day 27: Introduction to NoSQL databases (optional).
28. Day 28: Working with NoSQL databases (optional).

Day 29-30: Real-World Applications
29. Day 29: Building a simple application that uses SQL.
30. Day 30: Final review and practice, explore advanced topics in depth, or work on a personal project.

Remember to practice regularly, work on small projects, and use online resources and SQL platforms for hands-on experience. Adjust the plan based on your progress and interests, and you'll be well on your way to becoming proficient in SQL!

SQL for Data Analysis: https://t.me/SQLforDataAnalysisTP

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*Complete Roadmap to learn SQL in 2025* 👇👇

1. Basic Concepts
- Understand databases and SQL.
- Learn data types (INT, VARCHAR, DATE, etc.).

2. Basic Queries
- SELECT: Retrieve data.
- WHERE: Filter results.
- ORDER BY: Sort results.
- LIMIT: Restrict results.

3. Aggregate Functions
- COUNT, SUM, AVG, MAX, MIN.
- Use GROUP BY to group results.

4. Joins
- INNER JOIN: Combine rows from two tables based on a condition.
- LEFT JOIN: Include all rows from the left table.
- RIGHT JOIN: Include all rows from the right table.
- FULL OUTER JOIN: Include all rows from both tables.

5. Subqueries
- Use nested queries for complex data retrieval.

6. Data Manipulation
- INSERT: Add new records.
- UPDATE: Modify existing records.
- DELETE: Remove records.

7. Schema Management
- CREATE TABLE: Define new tables.
- ALTER TABLE: Modify existing tables.
- DROP TABLE: Remove tables.

8. Indexes
- Understand how to create and use indexes to optimize queries.

9. Views
- Create and manage views for simplified data access.

10. Transactions
- Learn about COMMIT and ROLLBACK for data integrity.

11. Advanced Topics
- Stored Procedures: Automate complex tasks.
- Triggers: Execute actions automatically based on events.
- Normalization: Understand database design principles.

12. Practice
- Use platforms like LeetCode, HackerRank, or learnsql for hands-on practice.

Here are some free resources to learn  & practice SQL 👇👇

More SQL Learning Resources: https://t.me/TechPsyche

Udacity free course- https://techurl.in/tYrRG

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Top 10 SQL Projects with Datasets: https://t.me/DataScienceResourcesTP/5

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ENJOY LEARNING 👍👍

Please go through this top 10 SQL projects with Datasets that you can practice and can add in your resume

📌1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)

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(https://www.kaggle.com/zynicide/wine-reviews)

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(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
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(https://www.kaggle.com/olistbr/brazilian-ecommerce)

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(https://www.kaggle.com/datasets?
search=inventory+management)

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(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)

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(https://www.kaggle.com/awaiskalia/banking-database)

📌9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)

🚀10. Analysis of Sales Data:
(https://www.kaggle.com/kyanyoga/sample-sales-data)

Small suggestion from my side for non tech students: kindly pick those datasets which you like the subject in general, that way you will be more excited to practice it, instead of just doing it for the sake of resume, you will learn SQL more passionately, since it’s a programming language try to make it more exciting for yourself.

Data Science Resources: https://t.me/DataScienceResourcesTP

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