Microsoft SQL Course
Master Microsoft SQL Server from the ground up — from writing your first SELECT query to building optimized, production-ready databases. This course covers everything from data filtering and joins to window functions, stored procedures, and Azure SQL. Whether you're breaking into data or leveling up your technical skills, you'll finish with real, job-ready SQL expertise.
What your team will master:
You'll start with relational database fundamentals and SQL Server setup, then move into filtering, sorting, and aggregating data with confidence. You'll learn how to join multiple tables, write subqueries, and use Common Table Expressions to handle complex data problems cleanly. The course covers data modification with INSERT, UPDATE, DELETE, and MERGE, along with transaction control and error handling. You'll also design database objects including tables, views, indexes, and stored procedures. Advanced topics include window functions, dynamic SQL, query optimization, and an introduction to Azure SQL for cloud deployments.
How your team learns in practice Microsoft SQL Course
How your team practices Microsoft SQL Course
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Course Content
8 Chapters • 32 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsIntroduction to SQL and Databases
Introduction to SQL and Databases
Lesson 1 • Relational Database Fundamentals
Covers tables, rows, columns, keys, and relationships as core database structures. Establishes the conceptual model students rely on throughout the course.
Lesson 2 • SQL Server Environment Setup
Guides installation and configuration of SQL Server and SQL Server Management Studio. Students gain a working local environment for all hands-on exercises.
Lesson 3 • Core SQL Language Categories
Introduces DDL, DML, DCL, and TCL as the four SQL command categories. Students understand which commands belong to each category before writing any queries.
Lesson 4 • Writing Your First SQL Queries
Teaches basic SELECT syntax to retrieve data from a single table. Students run their first queries and interpret result sets immediately.
Chapter 2HideHide detailsSee detailsFiltering, Sorting, and Basic Functions
Filtering, Sorting, and Basic Functions
Lesson 1 • Filtering Data with WHERE
Teaches comparison and logical operators inside WHERE clauses to restrict rows. Directly extends the SELECT queries introduced in Chapter 1.
Lesson 2 • Pattern Matching and Wildcards
Covers LIKE, wildcard characters, and ESCAPE for text-based filtering. Students filter string columns without knowing exact values.
Lesson 3 • Built-in Scalar Functions
Introduces string, numeric, and date scalar functions for transforming column values. Students apply functions directly inside SELECT and WHERE clauses.
Lesson 4 • Sorting Results with ORDER BY
Explains ascending and descending sort orders and multi-column sorting. Students control the presentation order of any query result set.
Chapter 3HideHide detailsSee detailsAggregation and Grouping Data
Aggregation and Grouping Data
Lesson 1 • Filtering Groups with HAVING
Distinguishes HAVING from WHERE and shows how to filter aggregated results. Students apply post-aggregation conditions to refine summary queries.
Lesson 2 • Aggregate Functions
Teaches COUNT, SUM, AVG, MIN, and MAX to compute summary statistics across rows. Builds directly on SELECT and WHERE skills from prior chapters.
Lesson 3 • Advanced Grouping Extensions
Introduces ROLLUP, CUBE, and GROUPING SETS for multi-level subtotals. Students generate cross-tabular summaries in a single query.
Lesson 4 • Grouping with GROUP BY
Explains how GROUP BY partitions rows before aggregation is applied. Students produce per-category summaries from any table.
Chapter 4HideHide detailsSee detailsJoining Multiple Tables
Joining Multiple Tables
Lesson 1 • Outer Joins
Covers LEFT, RIGHT, and FULL OUTER JOIN to include unmatched rows from one or both tables. Students handle optional relationships and detect missing data.
Lesson 2 • Multi-Table and Complex Joins
Extends joins to three or more tables and introduces non-equi joins. Students build queries that span entire normalized schemas.
Lesson 3 • Self Joins and Cross Joins
Explains joining a table to itself and generating Cartesian products with CROSS JOIN. Students solve hierarchical and combinatorial query problems.
Lesson 4 • INNER JOIN Fundamentals
Teaches INNER JOIN syntax and the ON condition to match rows across two tables. Students retrieve only rows with matching keys in both tables.
Chapter 5HideHide detailsSee detailsSubqueries and Common Table Expressions
Subqueries and Common Table Expressions
Lesson 1 • Scalar and Multi-Row Subqueries
Teaches subqueries in SELECT, WHERE, and FROM clauses returning single or multiple values. Students embed one query inside another to filter or compute dynamically.
Lesson 2 • Recursive CTEs
Covers anchor and recursive members to traverse hierarchical data like org charts. Students query parent-child structures without procedural loops.
Lesson 3 • Common Table Expressions
Introduces WITH clause CTEs as named, temporary result sets for cleaner query structure. Students replace nested subqueries with readable, maintainable CTE blocks.
Lesson 4 • Correlated Subqueries
Explains subqueries that reference the outer query's columns and re-execute per row. Students solve row-by-row comparison problems that joins cannot easily express.
Chapter 6HideHide detailsSee detailsData Modification and Transaction Control
Data Modification and Transaction Control
Lesson 1 • Inserting Data
Covers INSERT INTO with explicit values, SELECT results, and multi-row syntax. Students populate tables from both static values and existing query results.
Lesson 2 • Updating and Deleting Data
Teaches UPDATE and DELETE with WHERE conditions and join-based modifications. Students modify targeted rows while avoiding unintended full-table changes.
Lesson 3 • MERGE Statement
Introduces MERGE for upsert operations combining INSERT, UPDATE, and DELETE in one statement. Students synchronize a target table with a source data set efficiently.
Lesson 4 • Transactions and Error Handling
Explains BEGIN, COMMIT, and ROLLBACK transactions alongside TRY-CATCH error handling. Students protect data integrity during multi-step modification sequences.
Chapter 7HideHide detailsSee detailsDatabase Object Design and Management
Database Object Design and Management
Lesson 1 • Indexes and Query Performance
Introduces clustered and non-clustered indexes and their impact on read performance. Students choose and create indexes that accelerate common query patterns.
Lesson 2 • Views
Teaches creating, altering, and dropping views to encapsulate complex queries. Students expose simplified data interfaces without duplicating underlying tables.
Lesson 3 • Stored Procedures and Functions
Covers creating stored procedures, scalar functions, and table-valued functions for reusable logic. Students encapsulate business logic inside the database layer.
Lesson 4 • Creating and Altering Tables
Covers CREATE TABLE, data type selection, constraints, and ALTER TABLE modifications. Students design normalized table structures with enforced business rules.
Chapter 8HideHide detailsSee detailsAdvanced Query Techniques
Advanced Query Techniques
Lesson 1 • Query Optimization and Execution Plans
Teaches reading execution plans, identifying bottlenecks, and applying rewrites for performance. Students diagnose and resolve slow queries in real database workloads.
Lesson 2 • Pivoting and Unpivoting Data
Covers PIVOT and UNPIVOT operators to rotate rows into columns and vice versa. Students reshape data sets for reporting and cross-tabular analysis.
Lesson 3 • Window Functions
Teaches OVER, PARTITION BY, and ORDER BY to compute running totals, ranks, and moving averages. Students perform analytics without collapsing rows via GROUP BY.
Lesson 4 • Dynamic SQL
Explains building and executing SQL strings at runtime using EXEC and sp_executesql. Students handle variable schema names, dynamic filters, and parameterized execution.
Your valid completion certificate
This course is for you:
Business analyst: needs SQL to pull data independently without relying on engineers.
Career changer: moving into data roles and building technical skills from scratch.
Junior developer: wants to add database querying to an existing coding skill set.
Operations professional: manages data-heavy workflows and needs structured query knowledge.
Marketing analyst: tired of waiting on data teams to answer straightforward business questions.
Recent graduate: entering the job market and strengthening a resume with in-demand database skills.
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