SQL Course Contents.pdf

SQL Course Contents

• Think Like a Data Analyst: Understand relational databases, schemas, and primary/foreign key relationships.
• Extract Data on Demand: Write precise queries to pull exact datasets from millions of rows of raw information.
• Solve Real-World Business Problems: Filter, sort, and group data using WHERE, HAVING, and GROUP BY clauses.
• Merge Disconnected Data: Master advanced joins to combine data from different departments (e.g., sales, marketing, and HR) into single, unified reports.
• Build & Manage Databases: Create scalable tables, set up data constraints, and execute secure database updates.
• Optimize Query Performance: Write clean, efficient code capable of running smoothly on enterprise-grade servers.

💼 Career Outcomes

This course acts as a direct pathway to high-demand technical and analytical roles, including:
• Data Analyst / Business Intelligence (BI) Analyst
• Database Administrator (DBA)
• Junior Data Engineer / Backend Developer


 Structured Query Language.

Structured Query Language..jpg

SQL( Structured Query Language.)

1. Introduction to SQL •What is SQL? • History and evolution • RDBMS vs. NoSQL overview • SQL syntax basics • Common SQL dialects: MySQL, PostgreSQL, SQL Server, Oracle .2.Database Fundamentals • What is a database? • Tables, rows, columns • Data types (INT, VARCHAR, DATE, etc.) • Primary keys and foreign keys • Relational database design (Normalization basics).3. Basic SQL Operations • SELECT statement • WHERE clause • ORDER BY • LIMIT / TOP • Aliasing with AS4. Filtering and Conditional Logic • AND, OR, NOT • IN, BETWEEN, LIKE, IS NULL • CASE statements.5. Sorting and Aggregation • Aggregate functions: COUNT, SUM, AVG, MIN, MAX • GROUP BY and HAVING.6. Joins and Relationships • INNER JOIN • LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN • Self joins • Cross joins • Using aliases with joins.7. Subqueries and Nested Queries • Scalar subqueries • Correlated subqueries • EXISTS, IN, ANY, ALL.8. Data Manipulation Language (DML) • INSERT INTO • UPDATE • DELETE • MERGE (if applicable).9. Data Definition Language (DDL) • CREATE TABLE • ALTER TABLE • DROP TABLE • Constraints: NOT NULL, UNIQUE, DEFAULT, CHECK10. Indexing and Performance • Creating and using indexes • Understanding query execution plans • Optimizing SQL queries 11. Advanced SQL Topics • Window functions: ROW_NUMBER(), RANK(), LEAD(), LAG() • Common Table Expressions (CTEs) • Recursive queries • Pivot and unpivot12. Transactions and Concurrency • ACID properties • BEGIN, COMMIT, ROLLBACK • Locking and isolation levels13. Views and Stored Procedures • Creating and using views • Stored procedures and functions • Triggers14. SQL in Practice • Real-world data sets (e.g., employee, e-commerce) • Building reports and dashboards • Introduction to BI tools (optional: Power BI, Tableau, etc.) • SQL in Data Science workflows15. Final Project &amp; Assessment • Capstone project (build queries from a real-world database) • Query optimization exercises • Interview-style questions

SQL( Structured Query Language.)

SQL( Structured Query Language.)

About This Course

SQL( Structured Query Language.)