Modern SQL for Data Analysts: BigQuery in the AI Era

Build real-world SQL skills using BigQuery. Learn how to write, optimize, and debug queries in modern data workflows sha

What You will Learn

Learn how to write clean, structured SQL queries using BigQuery and real-world ecommerce datasets.
Understand how to sanity-check AI-generated SQL and identify common logic and performance issues.
Improve prompt engineering by thinking in SQL and communicating clearly with tools like ChatGPT or Copilot.
Build reliable analytics workflows using filters, joins, aggregations, subqueries, and CTEs.


Requirements

  • No prior SQL or programming experience required. You’ll need access to Google Cloud Platform with BigQuery enabled — a company account or personal free tier both work. Basic ability to navigate the GCP interface is enough.

Description

This course teaches you SQL for the real world — sharp, hands-on, and built for working with AI-powered tools like ChatGPT, Copilot, and Gemini.

Instead of just memorizing syntax, you’ll learn how to think in SQL. That means you can write better prompts, sanity-check AI-generated queries, and deliver faster — because you actually understand what good SQL looks like.

We use BigQuery and real ecommerce data to walk through each concept: selecting data, filtering, grouping, joining, aggregating, and building clean logic with CASE WHEN, subqueries, and CTEs.

Disclaimer : We utilized AI voices to give you the most natural and easy to follow narration throughout the course.

You’ll not only build technical skill, but also develop the reasoning and pattern awareness needed to interact effectively with AI systems in real workflows.

By the end, you’ll be able to:

  • Communicate clearly with AI tools by understanding query logic
  • Spot errors and bad assumptions in AI-generated SQL
  • Speed up your data work by blending prompting and hands-on writing
  • Build SQL workflows that are readable, testable, and production-friendly

This course is for:

  • Analysts, PMs, and engineers working with data
  • Beginners who want to skip fluff and learn how things actually work
  • Professionals using AI tools who want to prompt smarter
  • Anyone reviewing, modifying, or debugging AI-generated SQL

You’ll write code that makes sense. You’ll move faster with AI. And you’ll finally understand what’s going on under the hood.

Who this course is for:

  • Data analysts and product managers who work with AI tools and want to understand, edit, and validate SQL code.
  • Junior professionals or career switchers learning SQL for the first time and want a hands-on, real-world approach using BigQuery.
  • Engineers and analytics leads who review or integrate AI-generated SQL and need to sanity-check and improve query logic.
  • Anyone working in tech or data teams who wants to write better prompts, understand query output, and move faster in AI-powered workflows.

Course content

4 sections • 27 lectures • 1h 5m total length

  • Welcome to the Course
  • Is It Really Worth Learning SQL in the Age of AI?
  • Getting Started with BigQuery

  • Introduction to the Foundation Level
  • BigQuery UI Tour
  • Writing SELECT and FROM Queries
  • Your First SQL Code
  • Filtering Basics
  • Filtering Data with WHERE
  • Aggregating the Data
  • Aggregation Exercise
  • Grouping Data with GROUP BY
  • Group By Exercise
  • Creating Custom Columns
  • Foundation Level Quiz
  • Foundation Level Wrap Up

  • Introduction to the Intermediate Level
  • Introduction to Joins
  • Join Hands-on Exercise
  • Handling Duplicates
  • Handling NULL Values
  • Writing Conditional Logic with Case Statement
  • Case Statement Exercise
  • Introduction to Subqueries
  • Write cleaner code using CTEs
  • CTE coding exercise
  • Intermediate Level Quiz
  • Intermediate Level Wrap-up

  • Master Level Overview
  • Advanced Filtering Techniques
  • Saving Results to BigQuery
  • Introduction to Window Functions
  • Window Functions Exercise
  • Writing Cost-Efficient Queries
  • Clean SQL Code Principles
  • AI-Powered SQL Development Workflow
  • Course Wrap-Up



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