--- title: "SQL Fundamentals – Complete Course" id: "2366" type: "page" slug: "sql-fundamentals-complete-course" published_at: "2026-02-14T16:41:58+00:00" modified_at: "2026-02-14T16:41:58+00:00" url: "https://labs.postgreshelp.com/sql-fundamentals-complete-course/" markdown_url: "https://labs.postgreshelp.com/sql-fundamentals-complete-course.md" excerpt: "SQL Fundamentals – Complete PostgreSQL Training Course Duration: 40-60 hours | Level: Beginner to Intermediate | 12 Comprehensive Chapters Course […]" --- # SQL Fundamentals – Complete PostgreSQL Training Course **Duration:** 40-60 hours | **Level:** Beginner to Intermediate | **12 Comprehensive Chapters** ## Course Overview The SQL Fundamentals module is a comprehensive 12-chapter PostgreSQL training curriculum designed to take learners from SQL basics to advanced querying techniques. This course builds a strong foundation in Structured Query Language and relational database concepts using PostgreSQL as the teaching platform. **Target Audience:** Beginners to intermediate database professionals **Prerequisites:** Basic computer literacy; no prior SQL experience required **Delivery Format:** Hands-on with theory and practical exercises ## Complete Course Curriculum ### Chapter 01: Introduction to SQL and Relational Databases **Duration:** 3-5 hours **What You’ll Learn:** - SQL basics and declarative programming nature - Relational database fundamentals (tables, rows, columns) - Primary keys, foreign keys, and database relationships - PostgreSQL architecture and ACID compliance - SQL command categories (DDL, DML, DQL, DCL, TCL) - Basic SELECT syntax and queries - PostgreSQL-specific features (RETURNING, arrays, JSON) - SQL syntax rules and best practices **Key Topics:** - Declarative vs imperative languages - One-to-many, many-to-many, one-to-one relationships - Database schemas and namespaces - ACID properties (Atomicity, Consistency, Isolation, Durability) - Common beginner mistakes and how to avoid them ### Chapter 02: Data Manipulation Language (DML) **Duration:** 3-5 hours **What You’ll Learn:** - INSERT operations (single row, multiple rows, from SELECT) - UPDATE statements (basic, multiple columns, with calculations) - DELETE operations (basic, with conditions, using subqueries) - TRUNCATE vs DELETE comparison - UPSERT operations using ON CONFLICT clause - COPY operations for bulk data loading/export - Transaction basics (BEGIN, COMMIT, ROLLBACK) - Best practices for data modifications **Key Topics:** - DML statement execution - RETURNING clause for immediate results - Transaction atomicity - ON CONFLICT for duplicate handling - Bulk operations for performance optimization ### Chapter 03: Advanced Filtering & Sorting **Duration:** 3-5 hours **What You’ll Learn:** - WHERE clause mastery (comparison operators, BETWEEN, IN) - Pattern matching (LIKE, ILIKE, SIMILAR TO) - Regular expressions (POSIX operators) - NULL handling (IS NULL, IS NOT NULL) - Combining conditions (AND, OR, NOT) - DISTINCT for removing duplicates - ORDER BY (ascending, descending, multiple columns, expressions) - NULL handling in sorting (NULLS FIRST/LAST) - LIMIT and OFFSET for pagination - FETCH FIRST (SQL standard alternative) **Key Topics:** - Comparison and logical operators - Pattern matching with wildcards - Regular expressions in queries - NULL semantics in SQL - Pagination strategies and performance ### Chapter 04: Aggregations & Grouping **Duration:** 3-5 hours **What You’ll Learn:** - Aggregate functions (COUNT, SUM, AVG, MIN, MAX) - GROUP BY fundamentals and multiple column grouping - HAVING clause (filtering after aggregation) - Advanced aggregates (STRING_AGG, ARRAY_AGG, BOOL_AND/OR) - Statistical functions (STDDEV, VARIANCE, PERCENTILE) - ROLLUP, CUBE, and GROUPING SETS - GROUPING function - FILTER clause for conditional aggregation - Window functions in aggregation context **Key Topics:** - Aggregate computation semantics - GROUP BY rules and constraints - WHERE vs HAVING distinction - Advanced grouping operations - Performance optimization for aggregations ### Chapter 05: JOINs Mastery **Duration:** 4-6 hours **What You’ll Learn:** - INNER JOIN fundamentals - LEFT JOIN (LEFT OUTER JOIN) - RIGHT JOIN (RIGHT OUTER JOIN) - FULL JOIN (FULL OUTER JOIN) - CROSS JOIN and Cartesian products - SELF JOIN patterns - Multiple table joins - Complex join conditions (multiple conditions, OR conditions) - JOIN with aggregates - USING vs ON syntax - LATERAL JOIN (advanced) - Semi-join and anti-join patterns (EXISTS, NOT EXISTS) - JOIN performance optimization **Key Topics:** - Join mechanics and matching - NULL behavior in joins - Performance implications - Join vs subquery alternatives - Cartesian product prevention ### Chapter 06: Subqueries Deep Dive **Duration:** 4-5 hours **What You’ll Learn:** - Scalar subqueries (single value) - Row subqueries (single row, multiple columns) - Table subqueries (multiple rows) - Subqueries in SELECT, FROM, WHERE, HAVING clauses - Correlated vs non-correlated subqueries - IN/NOT IN operators - EXISTS/NOT EXISTS operators - ANY/SOME and ALL operators - Common patterns (finding duplicates, top-N queries, running totals) - Subquery performance issues and optimization - Lateral subqueries **Key Topics:** - Subquery execution and scoping - Correlated subquery performance - NULL handling in subqueries - Optimization strategies - When to use subqueries vs JOINs ### Chapter 07: Common Table Expressions (CTEs) **Duration:** 4-6 hours **What You’ll Learn:** - Basic CTE syntax (WITH clause) - Multiple CTEs in one query - CTE vs subquery comparison - Recursive CTEs fundamentals - Base case and recursive case patterns - Employee hierarchy traversal - Category tree structures - Factorial calculations - Graph traversal and pathfinding - Bill of Materials queries - CTE materialization (PostgreSQL 12+) - Performance considerations **Key Topics:** - CTE definition and scoping - Recursive query mechanics - Termination conditions - Graph algorithms in SQL - Named windows and code reusability ### Chapter 08: Window Functions Mastery **Duration:** 5-6 hours **What You’ll Learn:** - Window function basics and syntax - PARTITION BY and ORDER BY clauses - Ranking functions (ROW_NUMBER, RANK, DENSE_RANK, NTILE) - Navigation functions (LAG, LEAD, FIRST_VALUE, LAST_VALUE) - Aggregate window functions - Running totals and cumulative calculations - Moving averages and rolling sums - Frame specifications (ROWS vs RANGE) - Top-N per group patterns - Year-over-year growth calculations - Cumulative distribution functions - Gap and islands detection - Named windows for code reuse **Key Topics:** - Window semantics and execution - Frame boundaries and inclusivity - Ranking vs numbering - Performance characteristics - Window vs aggregate function differences ### Chapter 09: Advanced Data Types & Operations **Duration:** 5-6 hours **What You’ll Learn:** - JSON and JSONB (binary vs text) - Accessing and modifying JSON data - JSON operators and functions - JSONB indexing with GIN - Array types and operations - Array functions (unnest, array_agg, any, all) - Date and time types (DATE, TIME, TIMESTAMP, TIMESTAMPTZ) - Date arithmetic and functions - Interval types and calculations - Time zones handling - Range types (DATERANGE, TSRANGE, NUMRANGE) - UUID types - ENUM custom types - Composite types - Network address types (INET, CIDR) **Key Topics:** - Semi-structured vs structured data - Type system extensibility - Specialized data handling - Performance with advanced types - Indexing strategies for complex types ### Chapter 10: Transactions & Concurrency Control **Duration:** 4-5 hours **What You’ll Learn:** - Transaction basics (BEGIN, COMMIT, ROLLBACK) - ACID properties in depth - Isolation levels (Read Committed, Repeatable Read, Serializable) - Transaction phenomena (dirty reads, non-repeatable reads, phantom reads) - Explicit table locks - Row-level locks (FOR UPDATE, FOR SHARE, NOWAIT, SKIP LOCKED) - Advisory locks - Savepoints - Deadlock prevention and handling - Transaction timeouts - Practical examples (bank transfers, inventory reservation) - Monitoring transactions and locks - Serialization failure handling **Key Topics:** - Concurrency control mechanisms - Lock modes and compatibility - Deadlock detection - Consistency guarantees - Performance vs isolation trade-offs ### Chapter 11: Views & Materialized Views **Duration:** 3-5 hours **What You’ll Learn:** - Regular views (virtual tables) - Creating views with joins and aggregations - Modifying view definitions - Updatable views - View update rules and WITH CHECK OPTION - Materialized views (pre-computed results) - Refreshing materialized views - Concurrent refresh - View benefits (simplification, security, consistency) - View performance considerations - Cascading views - Indexing materialized views - Scheduling refreshes **Key Topics:** - Virtual vs physical storage - View optimization - Query rewriting - Materialization strategies - Security through views ### Chapter 12: SQL Best Practices & Optimization **Duration:** 4-6 hours **What You’ll Learn:** - Query optimization principles - Column selection best practices (avoiding SELECT *) - WHERE vs HAVING usage - Function impacts on indexes - Subquery optimization - Indexing strategies (foreign keys, frequent filters, composite indexes) - Partial indexes - Over-indexing and index monitoring - Transaction length management - Appropriate isolation level selection - Query writing with CTEs - Avoiding correlated subqueries - UNION ALL vs UNION - Batch operations - SQL injection prevention - Parameterized queries - Principle of least privilege - Row-level security - Code formatting and style - EXPLAIN ANALYZE usage - Slow query monitoring - Anti-patterns to avoid (EAV, delimited lists, FLOAT for money) **Key Topics:** - Query optimization principles - Index design strategies - Transaction management - Security best practices - Code quality and maintainability - Performance monitoring ## Learning Outcomes Upon completion of SQL Fundamentals, you will be able to: ✅ Write efficient SELECT queries with complex filtering, sorting, and aggregation ✅ Manipulate data using INSERT, UPDATE, DELETE, and UPSERT operations ✅ Join multiple tables and combine data using subqueries and CTEs ✅ Perform advanced analytics with window functions and recursive queries ✅ Work with PostgreSQL’s advanced data types (JSON, arrays, ranges) ✅ Implement transactions with appropriate isolation levels ✅ Design and optimize database queries ✅ Apply security best practices in SQL ✅ Use views for data abstraction and security ✅ Monitor and optimize database performance ## Prerequisites - Basic computer literacy - Understanding of databases (conceptual level) - Familiarity with command-line tools (helpful but not required) - **No prior SQL experience required** ## Course Format Each chapter includes: - **Theory:** Comprehensive notes with code examples - **Practical Examples:** Real-world scenarios and use cases - **Best Practices:** Tips, warnings, and anti-patterns highlighted - **Lab Exercises:** Hands-on practice exercises - **Solutions:** Detailed solutions with explanations - **Assessments:** Quizzes and hands-on projects ## Recommended Learning Path 1. **Foundation (Chapters 1-4):** Build core SQL skills – 12-20 hours 2. **Advanced Querying (Chapters 5-8):** Master complex queries – 16-23 hours 3. **Specialized Topics (Chapters 9-10):** Advanced data types and transactions – 8-11 hours 4. **Professional Skills (Chapters 11-12):** Views and best practices – 7-11 hours **Total Duration:** 40-60 hours (self-paced) ## Get Started Ready to master SQL? This course takes you from absolute beginner to confident SQL developer. Each chapter builds on the previous one, ensuring a solid foundation while progressively introducing advanced concepts. **Start with Chapter 01 and work your way through systematically for the best learning experience!** *Course Version: 1.0 | Platform: PostgreSQL 12+ | Updated: February 2026*