Applied SQL For Data Analytics / Data Science With BigQuery
Go from SQL Zero to Hero and develop rich mental models for writing sophisticated SQL statements & solving problems.
Description
Woah, another SQL course? Yes! Here's why this one is different.
We write 100% of the code together and I explain everything precisely and with abundant context. I have over a decade of industry experience over have taught this at the university level.
100% we do is application based. I rarely use toy data to illustrate points, unless it's more illustrative. Hopefully you'll learn much more than SQL throughout the course.
ZERO SET-UP. As long as you have a Google Account, you can login to BigQuery and get started immediately. No headaches configuring databases locally. You'll be up and running in under 3 minutes.
Spaced repetition to develop mastery. This is NOT a table of contents course. This is NOT a list of disparate exercises. Everything is connected. Concepts are revisited throughout the course so you can see them from different angles and maximize understanding.
Can you solve it? I provide tons of mini-challenges throughout the lecture material. The lecture material is basically us solving the problems. No time wasted on theory without context.
I'm not boring. I am human. I do make mistakes. I dwell on them so you can master the debugging process. Debugging is much more important than writing code.
What You Will Learn!
- SQL 101: The basics (SELECT, WHERE, HAVING, JOIN's, dealing with dates and timestamps)
- [NEW] Google Analytics 4 and BigQuery - Master the data model and attribution
- SQL 202: Date Handling, CASE statements, Common Table Expressions, Subqueries, Correlated Subqueries
- Develop clear models of translating business requirements to SQL
- Master Window / Analytic Functions, which are the power tools of modern data-science SQL
- 100% of videos are code along and provide numerous points to stop and "solve it" before me.
Who Should Attend!
- People with at least some SQL experience (you can write simple SELECT statements)
- Aspiring data scientists or data scientists who don't leverage SQL
- Data analysts
- Product managers who want to get better with DIY analysis.
- Developers who are interested in SQL!
- People interested in BigQuery that already know some SQL.
- Analysts needing to ramp up on GA4 BigQuery