Course description

1. Database Design: Understanding how to design efficient database schemas, tables, and relationships between them.

2. Querying Data: Writing SQL queries to retrieve, update, insert, and delete data from databases.

3. Data Manipulation: Using SQL commands to manipulate data, including sorting, filtering, aggregating, and joining data from multiple tables.

4. Indexes and Optimization: Implementing indexes to improve query performance and understanding techniques for optimizing database performance.

5. Transactions: Managing transactions to ensure data integrity and consistency.

6. Security: Implementing security measures such as user access control and ensuring data privacy.

7. Backup and Recovery: Performing database backups and understanding recovery procedures in case of data loss.

8. Integration: Integrating MySQL with other technologies and applications, such as web development frameworks or analytics tools.

9. Advanced Features: Exploring advanced MySQL features like stored procedures, triggers, and views for automating tasks and enhancing database functionality.

10. Scaling and High Availability: Strategies for scaling MySQL databases and ensuring high availability to handle large volumes of data and concurrent users.

Learning MySQL involves practical hands-on experience alongside theoretical knowledge to effectively manage and utilize relational databases for various applications and business needs.

What will i learn?

• Design Relational Databases: Build scalable databases from scratch by mastering normalization (up to 3NF) to minimize data redundancy and ensure data integrity.Write Complex SQL Queries: Fluently use Data Manipulation Language ($DML$) to extract, filter, sort, and aggregate data using SELECT, WHERE, GROUP BY, and HAVING clauses.Master Table Joins: Seamlessly merge data across multiple tables using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.Implement Data Safety & Integrity: Use Data Definition Language ($DDL$) to enforce constraints like PRIMARY KEY, FOREIGN KEY, UNIQUE, and NOT NULL to protect data quality.Optimize Query Performance: Use database indexing strategies and analyze execution plans using the EXPLAIN statement to speed up slow-running queries.Handle Complex Data Logistics: Write advanced subqueries, common table expressions ($CTEs$), and utilize built-in string, numeric, and date functions for deep data analysis.Build Automation Scripts: Create database triggers, stored procedures, and views to automate repetitive database tasks and streamline access patterns.

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