
SQL Bootcamp: From Zero to Job-Ready Course
Go from complete beginner to job-ready SQL professional with a curriculum built around real-world data tasks. Master everything from basic SELECT statements to advanced window functions, query optimization, and analytics workflows. This bootcamp gives you the technical skills and portfolio proof employers are actively hiring for.
What your team will master:
Write complex multi-table queries using INNER, OUTER, and self joins confidently.
Apply window functions to produce rankings, running totals, and period-over-period comparisons.
Design normalized relational schemas with constraints that enforce real-world business rules.
Optimize query performance by reading execution plans and implementing effective indexing strategies.
Build reusable analytical queries using CTEs, views, and modular SQL patterns.
Prepare for technical interviews with structured problem-solving methods and a public SQL portfolio.
How your team studies in practice SQL Bootcamp: From Zero to Job-Ready Course
How your team practices SQL Bootcamp: From Zero to Job-Ready Course
Professionals from these companies study at Dedika









Course content
8 Chapters • 38 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsRelational Databases and SQL Fundamentals
Relational Databases and SQL Fundamentals
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 5 • How Relational Databases Work
Covers tables, rows, columns, primary keys, and foreign keys as the structural backbone of relational data. Establishes the vocabulary used throughout every subsequent chapter.
Chapter 2HideHide detailsSee detailsData Types, NULL Handling, and Expressions
Data Types, NULL Handling, and Expressions
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 4 • Understanding and Handling NULL
Explains three-valued logic and why NULL comparisons require IS NULL and IS NOT NULL. Prevents silent bugs caused by misunderstood NULL behavior.
Chapter 3HideHide detailsSee detailsAggregation and Grouping Data
Aggregation and Grouping Data
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 4 • Core Aggregate Functions
Teaches COUNT, SUM, AVG, MIN, and MAX to summarize entire tables or filtered subsets. Provides the statistical building blocks used in every analytics query.
Chapter 4HideHide detailsSee detailsJoining Multiple Tables
Joining Multiple Tables
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 normalized 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 5 • Outer Joins and Unmatched Rows
Covers LEFT, RIGHT, and FULL OUTER JOIN to preserve unmatched rows from one or both tables. Critical for detecting missing relationships and data gaps.
Chapter 5HideHide detailsSee detailsSubqueries and Common Table Expressions
Subqueries and Common Table Expressions
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 5 • Common Table Expressions with WITH
Defines named result sets using WITH to replace nested subqueries with readable, reusable blocks. Dramatically improves query maintainability in production environments.
Chapter 6HideHide detailsSee detailsWindow Functions and Advanced Analytics
Window Functions and Advanced Analytics
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 5 • Ranking Functions
Applies ROW_NUMBER, RANK, DENSE_RANK, and NTILE to assign positional labels within partitions. Enables top-N analysis and percentile bucketing common in business reports.
Chapter 7HideHide detailsSee detailsData Modification and Schema Management
Data Modification and Schema Management
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 5 • Updating and Deleting Records
Applies UPDATE and DELETE with precise WHERE clauses to modify or remove targeted rows. Emphasizes safe practices to prevent accidental mass changes.
Chapter 8HideHide detailsSee detailsQuery Optimization and Job-Ready Practices
Query Optimization and Job-Ready Practices
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 optimization 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.
Lesson 5 • Views and Reusable Query Objects
Creates standard and materialized views to encapsulate complex logic and improve query reuse. Introduces the trade-offs between freshness and performance for each view type.
Your valid completion certificate
This course is for you:
Career changer: wants to move into data analytics from a non-technical field.
Marketing professional: needs SQL to pull campaign and customer data independently.
Business analyst: relies on others for data and wants full self-sufficiency.
Finance associate: works with large datasets and needs faster, more flexible querying.
Recent graduate: building job-ready technical skills before entering a competitive market.
Hobbyist developer: curious about databases and wants structured, practical SQL knowledge.
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