SQL Bootcamp: From Zero to Job-Ready Course

Lesson 1 • Core SELECT Statement Syntax

Teaches the SELECT, FROM, and WHERE clauses as the foundation of every SQL query. Students retrieve targeted rows and columns from a single table.

Lesson 2 • Sorting and Limiting Results

Introduces ORDER BY and LIMIT/FETCH to control result set size and sequence. Directly supports readable, efficient output in real-world queries.

Lesson 3 • Filtering with Logical Operators

Expands WHERE clauses using AND, OR, NOT, IN, BETWEEN, and LIKE for precise data retrieval. Builds the filtering toolkit students rely on in every subsequent chapter.

Lesson 4 • Setting Up Your SQL Environment

Guides installation of a local database engine and a GUI client so students can run queries immediately. Removes setup friction before any syntax is introduced.

Lesson 1 • Building Computed Columns

Uses arithmetic operators and string concatenation to derive new columns inside SELECT. Teaches students to enrich result sets without altering stored data.

Lesson 2 • Type Casting and Conversion

Covers CAST, CONVERT, and implicit coercion so students can transform values between types safely. Essential for joining mismatched columns and formatting output.

Lesson 3 • SQL Data Types Overview

Surveys numeric, text, date/time, and Boolean types and explains storage implications. Prevents type-mismatch errors that break queries in later chapters.

Lesson 1 • Rollups and Grouping Sets

Introduces ROLLUP, CUBE, and GROUPING SETS for multi-level subtotals in a single query. Prepares students for reporting queries that require hierarchical summaries.

Lesson 2 • Filtering Groups with HAVING

Distinguishes HAVING from WHERE and applies it to filter aggregated results. Enables queries like finding categories with more than a threshold number of records.

Lesson 3 • Grouping Results with GROUP BY

Applies GROUP BY to segment aggregates by one or more categorical columns. Connects aggregate functions to real segmentation tasks like sales by region.

Lesson 1 • INNER JOIN Fundamentals

Explains join predicates and how INNER JOIN returns only matching rows from both tables. Establishes the mental model for all other join types that follow.

Lesson 2 • Joining Three or More Tables

Chains multiple joins to traverse bridge tables and many-to-many relationships. Builds the skill needed for realistic schemas with normalised data.

Lesson 3 • Self Joins and Cross Joins

Demonstrates joining a table to itself for hierarchical data and CROSS JOIN for Cartesian products. Expands the join toolkit for less common but important scenarios.

Lesson 4 • Set Operations: UNION, INTERSECT, EXCEPT

Uses set operators to combine or compare result sets from separate queries. Complements joins by enabling row-level comparisons across datasets.

Lesson 1 • Subqueries in FROM Clauses

Creates derived tables by nesting a full SELECT in the FROM clause. Enables pre-aggregation and intermediate transformations before the outer query runs.

Lesson 2 • EXISTS and NOT EXISTS

Uses EXISTS to test for the presence of related rows without returning them. Offers a performant alternative to IN for large correlated datasets.

Lesson 3 • Scalar and Inline Subqueries

Embeds subqueries in SELECT and WHERE to compute single values or filter dynamically. Introduces the concept of query nesting before more complex forms.

Lesson 4 • Recursive CTEs for Hierarchical Data

Builds recursive CTEs to traverse parent-child trees such as org charts and category hierarchies. Extends CTE knowledge to advanced graph-traversal scenarios.

Lesson 1 • Offset Functions: LAG and LEAD

Uses LAG and LEAD to access values from preceding or following rows within a partition. Powers period-over-period comparisons and sequential change calculations.

Lesson 2 • Window Function Concepts and Syntax

Explains the OVER clause, partitioning, and ordering as the foundation of all window functions. Contrasts window functions with GROUP BY to clarify when each is appropriate.

Lesson 3 • Aggregate Window Functions

Runs SUM, AVG, COUNT, and similar functions over a sliding or cumulative window frame. Produces running totals and moving averages without subqueries.

Lesson 4 • FIRST_VALUE, LAST_VALUE, and NTH_VALUE

Retrieves boundary or positional values within a window frame for comparative analysis. Completes the window function toolkit with value-access functions.

Lesson 1 • Transactions and Atomicity

Wraps multi-statement operations in BEGIN, COMMIT, and ROLLBACK to guarantee all-or-nothing execution. Prevents partial updates that corrupt data integrity.

Lesson 2 • Inserting Data into Tables

Covers single-row and multi-row INSERT syntax, including INSERT from SELECT. Teaches safe data loading practices that prevent constraint violations.

Lesson 3 • Creating and Altering Tables

Uses CREATE TABLE and ALTER TABLE to define and evolve schema structures. Introduces column constraints and data type choices that enforce data integrity.

Lesson 4 • Constraints and Referential Integrity

Defines PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, and NOT NULL constraints to enforce business rules at the database level.

Lesson 1 • Indexing Strategies for Performance

Covers B-tree, composite, partial, and covering indexes and explains when each type helps. Teaches index selection as a balance between read speed and write overhead.

Lesson 2 • Professional SQL Coding Standards

Establishes formatting, naming conventions, commenting, and version control habits expected in professional data teams. Prepares students for code review and collaborative workflows.

Lesson 3 • Reading and Interpreting Execution Plans

Uses EXPLAIN and EXPLAIN ANALYZE to read query plans and identify bottlenecks. Connects plan output to concrete optimisation decisions in subsequent sections.

Lesson 4 • Writing Efficient Query Patterns

Identifies anti-patterns such as SELECT *, functions on indexed columns, and implicit conversions that degrade performance. Replaces each with a faster alternative.