Structured Query Language (SQL) is the backbone of data handling across industries, making it a vital skill for developers, analysts, data scientists, and IT professionals. This course, "Mastering SQL – From Fundamentals to Advanced Querying," is designed to take learners from the foundational concepts of relational databases to advanced SQL techniques used in enterprise environments.

Whether you're a beginner with no prior experience or a developer looking to deepen your database querying skills, this course offers a comprehensive, hands-on approach to understanding and applying SQL in real-world scenarios.

By the end of the course, you’ll not only be able to write complex queries but also interpret, optimize, and debug them effectively—skills that are indispensable in data-driven roles.

Target Audience

This course is designed for:

• Aspiring data analysts and data scientists

• Backend and full-stack developers

• IT professionals and database administrators

• Business analysts and product managers

• Students and graduates in computer science or data-related fields

No prior knowledge of SQL or databases is required, though basic programming logic will be helpful.

Course Objectives

Upon successful completion of this course, learners will be able to:

• Understand the structure and functionality of relational databases

• Design, query, and manage databases using SQL

• Write and optimize SQL queries for CRUD operations (Create, Read, Update, Delete)

• Perform advanced queries using JOINs, subqueries, and set operations

• Apply grouping, filtering, and aggregation functions

• Use window functions and common table expressions (CTEs)

• Work with date and string functions to manipulate and analyze data

• Ensure data integrity using constraints and transactions

• Identify and resolve performance bottlenecks in SQL queries

Course Modules

Module 1: Introduction to Relational Databases

• What is a database?

• Understanding relational models

• Tables, rows, columns, and keys (Primary, Foreign)

• Introduction to SQL as a query language

Module 2: Getting Started with SQL

• Setting up a database environment (MySQL/PostgreSQL/SQLite)

• Using an SQL client or interface

• SELECT statements and filtering data with WHERE

• Sorting results with ORDER BY

• Limiting results with LIMIT and OFFSET

Module 3: Data Definition Language (DDL)

• Creating and modifying tables (CREATE, ALTER, DROP)

• Data types and column attributes

• Constraints (NOT NULL, UNIQUE, DEFAULT, CHECK)

• Primary and foreign key relationships

Module 4: Data Manipulation Language (DML)

• Inserting data into tables

• Updating records

• Deleting records safely

• Best practices for data integrity

Module 5: Working with Functions and Operators

• Arithmetic and logical operators

• String functions (CONCAT, LENGTH, SUBSTRING, etc.)

• Numeric functions (ROUND, CEIL, FLOOR)

• Date/time functions (NOW, DATE_ADD, DATEDIFF, etc.)

Module 6: Aggregation and Grouping

• COUNT, SUM, AVG, MIN, MAX

• GROUP BY and HAVING clauses

• Filtering aggregated results

• Nested aggregation and derived columns

Module 7: JOINS – Combining Data from Multiple Tables

• INNER JOIN vs LEFT/RIGHT/FULL OUTER JOIN

• CROSS JOIN and SELF JOIN

• Best practices for writing efficient joins

• Real-world join scenarios (orders, users, products)

Module 8: Subqueries and Set Operations

• Scalar, correlated, and inline subqueries

• Using subqueries in WHERE, FROM, and SELECT clauses

• Set operations: UNION, INTERSECT, EXCEPT

• Performance considerations for subqueries

Module 9: Advanced SQL Techniques

• Common Table Expressions (CTEs) and recursive queries

• Window functions: RANK, DENSE_RANK, ROW_NUMBER, LEAD/LAG

• Analytical queries using PARTITION BY and ORDER BY

• Working with views and materialized views

Module 10: Transactions and Data Integrity

• Understanding transactions and ACID properties

• BEGIN, COMMIT, ROLLBACK

• Using constraints and triggers

• Handling concurrency and locking

Module 11: Query Optimization and Best Practices

• Indexing and its impact on performance

• EXPLAIN plans and interpreting them

• Writing readable, maintainable SQL

• Common pitfalls and how to avoid them

Module 12: Capstone Project

• Design a normalized database schema

• Populate the database with realistic sample data

• Write a series of queries to generate business insights

• Present your project as a report or dashboard-ready dataset