Seven parts covering the full beginner SQL toolkit — retrieval, pattern matching, NULL handling, aggregation, joins, and advanced filtering — with an AI-assisted editor, an on-demand AI tutor, and a hands-on capstone project.
Every part runs on real tables — students, courses, instructors, enrollments — no lecture-only modules.
Write and run SQL directly in the course, with AI prompting built into the editor so you practice live, not just read about it.
Stuck on a query? The built-in AI tutor gives guided hints and asks you questions to get you unstuck — it won't just hand you the answer.
Not built for memorizing commands. The focus is understanding what each one does and why — memorization follows naturally through practice.
SQL Beginner is the first course in a three-course sequence — Beginner, Intermediate, Advanced — where each course builds directly on the one before it. Seven parts follow the natural progression of a real query: from selecting columns, to filtering rows, to handling missing data, to summarizing and combining tables. Students aren't expected to memorize commands; the emphasis is on understanding what each one does and why, so memorization follows naturally through practice.
Seven parts that follow the natural progression of a query — from selecting columns, to filtering rows, to handling missing data, to summarizing and combining tables. Part 7 is optional, for learners heading toward database or data management work.
The five commands that appear in virtually every SQL query. Understanding each one deeply is the most important investment in the course.
Extends WHERE with more expressive filtering tools, and introduces the habits that make queries readable and maintainable.
NULL, CASE, and null-handling functions — how to recognize, filter, and clean missing data before it reaches a report.
Turning rows into summaries — counts, totals, and averages grouped by category.
Connecting and stacking tables — the point where SQL becomes genuinely powerful for multi-table questions.
Filtering grouped results and checking subquery conditions — the most important conceptual leap in the course.
Three data modification commands that go beyond reading data. Optional, but important for learners heading toward database or data management roles.
Every part follows the same hands-on pattern. Here's an excerpt from Part 3: Missing Values & Conditional Logic — the actual concept explanation and worked examples students work through in the course editor.
A NULL value means no data, missing data, or unknown data. It does not mean zero, an empty string, or "nothing" — it literally means "we don't have a value for this yet." NULL behaves differently from normal values: you can't compare it with = or <>, and any calculation involving NULL becomes NULL too. NULL is like that one student who never answers emails — you don't know if they're absent, or just ignoring you.
Beginners often try to check for missing values with a normal equals sign — but SQL treats NULL as a special case that = can't catch.
Question: Show each student's email, replacing missing ones with "No Email."
Null-handling functions are like having a backup plan: "if this doesn't work, try that, and if all else fails, use this." COALESCE is the most universal version — it works across every major SQL system.
No formal prerequisite is required — no coding or database experience needed. If you'd prefer a visual, concept-first introduction before this course, SQL Basics is a good starting point.
SQL Basics teaches the core six-keyword workflow visually, with diagrams and side-by-side comparisons. SQL Beginner is broader and more command-focused — seven parts covering pattern matching, NULL handling, CASE logic, and optional data modification commands, as Course 1 of the Beginner → Intermediate → Advanced sequence.
Real tables — students, courses, instructors, and enrollments — used consistently across all seven parts, including realistic missing/NULL values so you practice handling messy data, not just clean examples.
The built-in AI tutor is available on every task. Ask it what's wrong and it responds with a guided hint or question — not the direct answer — so you build the debugging skill instead of just copying a fix.
Yes. The course ends with a hands-on capstone project that applies retrieval, filtering, NULL handling, aggregation, and joins together — the same kind of query a working analyst would write.
Most learners complete the seven parts in 4–6 weeks at a few hours per week. Since the course is self-paced, you can move faster or slower based on your schedule.
Yes. On completion, you'll receive a certificate of completion from the Canadian Institute of Artificial Intelligence (CiAI) that you can add to your resume or LinkedIn profile.
SQL Intermediate is next, covering subqueries, CTEs, advanced filtering, and data cleaning. SQL Advance follows after that, covering performance, window functions, and analytics engineering.
Yes. The course is billed monthly, and you can cancel at any time without losing access to material you've already completed.
Seven structured parts, real hands-on practice, an AI tutor when you're stuck, and a capstone project to prove what you've learned.