| 1 - Introduction to the Foundation Level.html | 1.7 KB | ||
| 1 - Introduction to the Intermediate Level.html | 2.7 KB | ||
| 1 - Master Level Overview.html | 2.2 KB | ||
| 1 -Advanced Filtering Techniques.mp4 | 21.9 MB | ||
| 1 -BigQuery UI Tour.mp4 | 12 MB | ||
| 1 -Introduction to Joins.mp4 | 23 MB | ||
| 1 -Welcome to the Course.mp4 | 55.4 MB | ||
| 2 - Saving Results to BigQuery.html | 5.2 KB | ||
| 2 -Handling Duplicates.mp4 | 18.3 MB | ||
| 2 -Introduction to Window Functions.mp4 | 18.9 MB | ||
| 2 -Is It Really Worth Learning SQL in the Age of AI.mp4 | 55.3 MB | ||
| 2 -Writing SELECT and FROM Queries.mp4 | 28.5 MB | ||
| 3 -Filtering Basics.mp4 | 26.5 MB | ||
| 3 -Getting Started with BigQuery.mp4 | 15.5 MB | ||
| 3 -Handling NULL Values.mp4 | 13.1 MB | ||
| 3 -Writing Cost-Efficient Queries.mp4 | 7.6 MB | ||
| 4 -Aggregating the Data.mp4 | 20.6 MB | ||
| 4 -Clean SQL Code Principles.mp4 | 12.6 MB | ||
| 4 -Writing Conditional Logic with Case Statement.mp4 | 17.8 MB | ||
| 5 -AI-Powered SQL Development Workflow.mp4 | 12.7 MB | ||
| 5 -Grouping Data with GROUP BY.mp4 | 22.7 MB | ||
| 5 -Introduction to Subqueries.mp4 | 12.5 MB | ||
| 6 -Course Wrap-Up.mp4 | 23.6 MB | ||
| 6 -Creating Custom Columns.mp4 | 8 MB | ||
| 6 -Write cleaner code using CTEs.mp4 | 14.6 MB | ||
| 7 - Foundation Level Wrap Up.html | 921.6 B | ||
| 7 - Intermediate Level Wrap-up.html | 512 B | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 29 total files | |||
Modern SQL for Data Analysts: BigQuery in the AI Era
https://WebToolTip.com
Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 5m | Size: 441 MB
Build real-world SQL skills using BigQuery. Learn how to write, optimize, and debug queries in modern data workflows sha
What you'll 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 logicSpot errors and bad assumptions in AI-generated SQLSpeed up your data work by blending prompting and hands-on writingBuild SQL workflows that are readable, testable, and production-friendlyThis course is for:Analysts, PMs, and engineers working with dataBeginners who want to skip fluff and learn how things actually workProfessionals using AI tools who want to prompt smarterAnyone reviewing, modifying, or debugging AI-generated SQLYou’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.
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