1. SQL Basics:

   Introduction To Different Types of Queries.

2. Data Retrieval:

   SELECT statements for data retrieval

   Filtering data using WHERE clause

   Sorting data using ORDER BY

   Limiting results using LIMIT and OFFSET

   LIKE BETWEEN AND IN, EXISTS, or ANY/ALL

   Subqueries and nested queries

   Working with multiple tables in MySQL

   JOIN

3. Data Modification:

   INSERT, UPDATE, and DELETE statements

   Transaction management (BEGIN, COMMIT, ROLLBACK)

4. Aggregation:

   GROUP BY clause for grouping data

5. Data Manipulation (Build-in Functions):

   String functions

   Numeric Functions

   Date and Time Functions

   Aggregate Functions

   Control Flow Functions

   Mathematical Functions

   Bit functions

   Encryption and Hashing Functions

   JSON (JavaScript Object Notation) functions

6. Indexes and Performance Optimization:

   • Indexing in MySQL (B-tree indexes)
   • Query optimization techniques
   • EXPLAIN statement for query analysis
   • Using appropriate indexes for efficient querying

7. Data Import and Export:

   • Importing data from CSV and other formats
   • Exporting data to CSV, JSON, and other formats
   • mysqldump and MySQL data dump utilities

8. Stored Procedures and Functions:

   • Creating and executing stored procedures
   • Creating and executing user-defined functions
   • Advantages of using stored procedures

9. Data Security and User Management:

   • Creating and managing user accounts
   • Granting and revoking privileges
   • Securing MySQL databases and connections

10. Normalization and Database Design:

    • Principles of database normalization (1NF, 2NF, 3NF)
    • Designing efficient database schemas

11. Views and Subqueries:

    • Creating and using views
    • Using subqueries in SQL statements

12. Advanced Topics:

    • Handling NULL values
    • Triggers and events
    • Full-text search
    • Geospatial data and spatial indexing

13. Connecting MySQL with Data Science Tools:

    SQL Magic

    • Integrating MySQL with data analysis and visualization libraries (e.g., pandas, Matplotlib)

14. Scaling and Replication:

    • Scaling MySQL for large datasets
    • MySQL replication for data redundancy and load balancing

15. Database Backup and Recovery:

    • Regular database backups and recovery strategies

16. MySQL Performance Tuning for Data Science:

    • Optimizing MySQL for data-intensive operations
    • Monitoring and profiling MySQL performance

These topics cover a broad range of MySQL concepts and skills that are essential for data scientists and analysts working with relational databases. Understanding MySQL allows data professionals to efficiently store, retrieve, and manipulate data for various analytical tasks.