
PostgreSQL Course
Master PostgreSQL from the ground up — from writing your first query to administering production databases. This course covers everything a developer or DBA needs: schema design, query optimisation, transactions, replication, and advanced features. Build real, job-ready skills with hands-on practice at every step.
What your team will master:
You will learn how to design relational schemas, write complex multi-table queries, and tune them for maximum performance using indexes and execution plans. The course covers transactions, MVCC, and concurrency control so your applications handle real-world workloads safely. You will work with PostgreSQL-specific features including JSONB, window functions, full-text search, and table partitioning. Administration topics include user roles, backup strategies, replication, and connection pooling. By the end, you will have the skills to build, optimise, and maintain PostgreSQL databases in production environments.
How your team learns in practice PostgreSQL Course
How your team practises PostgreSQL Course
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Course content
8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsIntroduction to PostgreSQL and Relational Databases
Introduction to PostgreSQL and Relational Databases
Lesson 1 • Installing and Configuring PostgreSQL
Guides installation on major operating systems and initial server configuration. Students gain a working local environment for all hands-on exercises.
Lesson 2 • Using psql and pgAdmin
Introduces the psql command-line interface and the pgAdmin graphical tool. Students can execute queries and browse database objects using both interfaces.
Lesson 3 • Creating Your First Database and Tables
Demonstrates CREATE DATABASE, CREATE TABLE, and basic data insertion. Ties architecture concepts to practical object creation within a live PostgreSQL instance.
Lesson 4 • Relational Database Fundamentals
Covers tables, rows, columns, keys, and relationships as the basis of relational design. Establishes the conceptual framework needed for all subsequent PostgreSQL work.
Lesson 5 • PostgreSQL Architecture and Components
Explains the client-server model, process structure, and storage layout of PostgreSQL. Provides the mental model required to understand query execution and administration.
Chapter 2HideHide detailsSee detailsSQL Querying Essentials in PostgreSQL
SQL Querying Essentials in PostgreSQL
Lesson 1 • Working with PostgreSQL Data Types
Explores numeric, text, boolean, date/time, and JSON types specific to PostgreSQL. Correct type selection improves storage efficiency and query accuracy.
Lesson 2 • Sorting, Limiting, and Paging Results
Teaches ORDER BY, LIMIT, and OFFSET for controlling result sets. Directly supports pagination patterns used in application development.
Lesson 3 • Inserting, Updating, and Deleting Data
Covers DML commands INSERT, UPDATE, DELETE, and TRUNCATE with safe practices. Students can maintain table data while avoiding accidental mass changes.
Lesson 4 • Selecting and Filtering Data
Covers SELECT, WHERE, comparison operators, and logical connectors. Forms the foundation for every query written throughout the course.
Lesson 5 • Aggregation and Grouping
Introduces aggregate functions and GROUP BY for summarising data. Enables students to produce reports and metrics directly from raw tables.
Chapter 3HideHide detailsSee detailsJoins, Subqueries, and Set Operations
Joins, Subqueries, and Set Operations
Lesson 1 • Set Operations: UNION, INTERSECT, EXCEPT
Teaches combining result sets with set operators and their ALL variants. Enables students to merge or compare outputs from structurally similar queries.
Lesson 2 • Advanced Filtering Techniques
Covers ANY, ALL, EXISTS, and lateral joins for sophisticated row selection. Extends filtering vocabulary beyond basic WHERE conditions.
Lesson 3 • Common Table Expressions
Introduces WITH clauses (CTEs) for readable, modular query construction. Students refactor complex nested queries into maintainable CTE chains.
Lesson 4 • Subqueries and Derived Tables
Covers scalar, row, and table subqueries in SELECT, FROM, and WHERE clauses. Builds query composition skills needed for advanced filtering and transformation.
Lesson 5 • Understanding and Writing Joins
Explains INNER, LEFT, RIGHT, FULL OUTER, and CROSS joins with visual diagrams. Students select the correct join type for any multi-table query scenario.
Chapter 4HideHide detailsSee detailsDatabase Design and Schema Management
Database Design and Schema Management
Lesson 1 • Schemas, Namespaces, and Search Path
Explains PostgreSQL schemas as namespaces and the search_path setting. Students organise objects across schemas for multi-tenant or modular applications.
Lesson 2 • Constraints and Data Integrity
Explains NOT NULL, UNIQUE, CHECK, PRIMARY KEY, and FOREIGN KEY constraints. Enforcing integrity at the database level prevents invalid data from entering tables.
Lesson 3 • Altering and Evolving Schemas
Teaches ALTER TABLE operations and safe schema migration strategies. Students modify live schemas without causing downtime or data loss.
Lesson 4 • Sequences and Auto-Generated Keys
Covers SERIAL, BIGSERIAL, and GENERATED ALWAYS AS IDENTITY for surrogate keys. Students choose the appropriate key generation strategy for each table.
Lesson 5 • Normalisation and Schema Design Principles
Covers 1NF through 3NF and practical denormalisation trade-offs. Students evaluate schema designs for redundancy and update anomalies.
Chapter 5HideHide detailsSee detailsIndexes and Query Performance
Indexes and Query Performance
Lesson 1 • Reading EXPLAIN and EXPLAIN ANALYZE
Teaches interpreting execution plans, node types, and actual vs. estimated rows. Students identify bottlenecks in query plans and prioritise optimisation efforts.
Lesson 2 • B-Tree and Other Index Types
Covers B-Tree, Hash, GIN, GiST, and BRIN indexes with appropriate use cases. Students select the correct index type based on data characteristics and query patterns.
Lesson 3 • How PostgreSQL Executes Queries
Explains the parser, planner, and executor pipeline and cost-based optimisation. Understanding this pipeline is prerequisite to interpreting EXPLAIN output.
Lesson 4 • Query Optimisation Strategies
Applies rewriting techniques, statistics tuning, and planner hints to improve performance. Students resolve common anti-patterns such as implicit casts and function wrapping.
Lesson 5 • Creating and Managing Indexes
Demonstrates CREATE INDEX options including partial, expression, and covering indexes. Students build indexes that maximise query speed while minimising write overhead.
Chapter 6HideHide detailsSee detailsTransactions, Concurrency, and Locking
Transactions, Concurrency, and Locking
Lesson 1 • Handling Concurrency Conflicts
Addresses optimistic vs. pessimistic locking strategies and retry logic. Students implement patterns that handle concurrent updates without data corruption.
Lesson 2 • Transaction Fundamentals
Covers BEGIN, COMMIT, ROLLBACK, and SAVEPOINT for atomic data changes. Students wrap multi-step operations in transactions to guarantee consistency.
Lesson 3 • Locking Mechanisms
Covers table-level, row-level, and advisory locks and their acquisition modes. Students prevent deadlocks and minimise lock contention in concurrent workloads.
Lesson 4 • MVCC and Isolation Levels
Explains Multi-Version Concurrency Control and the four SQL isolation levels. Students choose isolation levels that balance consistency requirements with throughput.
Lesson 5 • Vacuum, Bloat, and MVCC Maintenance
Explains dead tuple accumulation, VACUUM, and autovacuum configuration. Students keep tables healthy and prevent transaction ID wraparound in long-running systems.
Chapter 7HideHide detailsSee detailsAdvanced PostgreSQL Features
Advanced PostgreSQL Features
Lesson 1 • Window Functions
Covers OVER, PARTITION BY, ORDER BY, and frame clauses for analytical queries. Students compute running totals, rankings, and moving averages without self-joins.
Lesson 2 • Arrays, Ranges, and Composite Types
Explores PostgreSQL array operators, range types, and user-defined composite types. Students model complex data structures natively without auxiliary tables.
Lesson 3 • Table Partitioning
Covers range, list, and hash partitioning strategies and partition pruning. Students partition large tables to improve query performance and simplify data lifecycle management.
Lesson 4 • JSON and JSONB Data Handling
Teaches storing, querying, and indexing semi-structured data with JSONB operators. Students integrate document-style data into relational schemas effectively.
Lesson 5 • Full-Text Search
Introduces tsvector, tsquery, and ranking functions for natural-language search. Students build search features that outperform LIKE-based pattern matching.
Chapter 8HideHide detailsSee detailsPostgreSQL Administration and Security
PostgreSQL Administration and Security
Lesson 1 • Backup and Restore Strategies
Teaches pg_dump, pg_restore, and pg_basebackup for logical and physical backups. Students design backup schedules that meet recovery time and point objectives.
Lesson 2 • Server Monitoring and Diagnostics
Uses system catalog views, pg_stat_* views, and logging to monitor server health. Students detect and respond to performance degradation before it impacts users.
Lesson 3 • Connection Pooling and Scaling
Covers connection overhead, PgBouncer pooling modes, and read replica routing. Students configure pooling to support high-concurrency application workloads.
Lesson 4 • Write-Ahead Logging and Replication
Explains WAL mechanics and configures streaming replication for high availability. Students set up a primary-standby pair and verify replication lag.
Lesson 5 • Roles, Privileges, and Row-Level Security
Covers CREATE ROLE, GRANT, REVOKE, and row-level security policies. Students implement least-privilege access control for multi-user and multi-tenant systems.
Your valid completion certificate
This course is for you:
Backend developers wanting to move beyond basic SQL knowledge.
Junior DBAs ready to take ownership of real production databases.
Data analysts who need stronger querying and schema skills.
Software engineering students building their first data-driven applications.
Career changers entering tech roles that require database expertise.
DevOps engineers who manage PostgreSQL but lack formal database training.
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