🎯 Course Goals

  • Understand relational databases and SQL fundamentals.

  • Write efficient queries to extract, filter, and analyze data.

  • Perform joins, subqueries, aggregations, and window functions.

  • Work with real-world databases for business use-cases.

  • Optimize queries, design schemas, and understand transactions.

  • Prepare for SQL interviews and certifications.

🏗 Course Structure

Duration: 8–10 weeks (self-paced)
Format: Video lessons, quizzes, exercises, projects, and case studies

📂 Modules & Lessons

Module 1: Introduction to Databases & SQL

  1. What is a Database? (RDBMS, NoSQL, OLTP vs OLAP)

  2. Understanding Tables, Rows, and Columns

  3. Introduction to SQL (DDL, DML, DCL, TCL)

  4. Installing SQL Environment (MySQL / PostgreSQL / SQL Server / SQLite)

  5. Your First Query (SELECT * FROM table;)

Exercise: Connect to a sample database and retrieve data.
Quiz: Identify the correct SQL command for different scenarios.

Module 2: SQL Basics – Data Retrieval

  1. SELECT Statement Basics

  2. Filtering with WHERE

  3. Sorting with ORDER BY

  4. Limiting Results with LIMIT / TOP

  5. Aliases (AS)

Exercise: Retrieve top 10 employees earning more than $50k.

Module 3: Filtering & Operators

  1. Logical Operators (AND, OR, NOT)

  2. Comparison Operators (=, <, >, BETWEEN, IN)

  3. Pattern Matching with LIKE & Wildcards

  4. Dealing with NULL Values

Mini Project: Create a query to filter customer orders in a given date range.

Module 4: Aggregations & Grouping

  1. Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)

  2. Grouping with GROUP BY

  3. Filtering Groups with HAVING

  4. Combining Aggregations with Conditions

Project: Sales analysis – Find average order value per region.

Module 5: Joins & Relationships

  1. Understanding Keys (Primary, Foreign)

  2. INNER JOIN

  3. LEFT JOIN & RIGHT JOIN

  4. FULL OUTER JOIN

  5. SELF JOIN

  6. CROSS JOIN

Case Study: Employee–Department Database (fetch employees with their department names).

Module 6: Subqueries & Advanced Filtering

  1. Single-Row Subqueries

  2. Multi-Row Subqueries (IN, ANY, ALL)

  3. Correlated Subqueries

  4. EXISTS vs NOT EXISTS

Exercise: Find customers who placed more than 5 orders.

Module 7: Advanced SQL Functions

  1. String Functions (CONCAT, SUBSTRING, REPLACE, TRIM)

  2. Date & Time Functions (NOW, DATEADD, DATEDIFF)

  3. Mathematical Functions (ROUND, CEIL, FLOOR)

  4. CASE & IF Statements

Mini Project: Create a sales report with “Low/Medium/High” value classification.

Module 8: Window Functions

  1. Introduction to Window Functions

  2. ROW_NUMBER(), RANK(), DENSE_RANK()

  3. NTILE(), Running Totals, Moving Averages

  4. Partitioning Data with PARTITION BY

Case Study: Ranking top 3 products per category by sales.

Module 9: Database Management & Design

  1. Creating & Dropping Databases/Tables

  2. Data Types (INT, VARCHAR, DATE, etc.)

  3. Constraints (PRIMARY KEY, UNIQUE, DEFAULT, CHECK)

  4. Normalization & Schema Design (1NF, 2NF, 3NF, BCNF)

  5. Indexing Basics

Exercise: Create a normalized database for an e-commerce store.

Module 10: Transactions & Security

  1. What is a Transaction? (BEGIN, COMMIT, ROLLBACK)

  2. ACID Properties

  3. Isolation Levels

  4. SQL Injection & Prevention

  5. User Roles & Permissions

Lab: Simulate a banking transfer with rollback on error.

Module 11: Query Optimization

  1. Understanding Execution Plans

  2. Indexing Strategies

  3. Avoiding Common Pitfalls (SELECT *)

  4. Optimizing Joins & Subqueries

  5. Denormalization for Performance

Case Study: Optimize slow-running queries in a sales database.

Module 12: Real-World Projects

  1. Project 1: HR Database Analysis

    • Find employee turnover rates, salary distribution, and hiring trends.

  2. Project 2: E-commerce Database

    • Sales analysis, top customers, product trends.

  3. Project 3: Banking Transactions

    • Fraud detection with unusual transaction patterns.

  4. Project 4: Social Media Analytics

    • Top posts, engagement rates, user retention.

Module 13: SQL for Data Science & Business

  1. Using SQL with Excel / Power BI / Tableau

  2. SQL for Machine Learning (Feature Extraction)

  3. Common Interview Questions

  4. SQL Certifications (Microsoft, Oracle, PostgreSQL, Google BigQuery)

Last modified: Thursday, 18 September 2025, 2:49 PM