Compare analytics engineering training plans.
Start free, buy the practice library, or follow a diagnostic-shaped path through browser-run SQL and Python, guided modeling, dbt, API, and data-quality scenarios, to a human-reviewed capstone.
- Free
- $0
- Practice
- $149
- Course
- $997
Free
Free forever · No credit card
- Curated free SQL, Python, and dataset exercises
- All 105 free resource articles
- Roadmap and syllabus preview
- Topic hubs across SQL, dbt, modeling, BigQuery, and Python
Practice Pass
One payment · Lifetime access
The full practice library with hints and worked solutions. No capstone or GPT tutor — that's the full course.
- All 1,604 graded exercises
- 49 topics, hints + worked solutions
- SQL Rapid-Fire, unlimited
- Lifetime access
Analytics Engineering Mastery
One payment · Lifetime access · 7-day refund
- 89 core lessons in a personalized path
- 1,604 graded exercises across 49 topics
- SQL and Python that run and grade in the browser
- Guided dbt, modeling, and data-quality scenarios with worked answers
- 22 hands-on practice challenges and applied labs
- 1 human-reviewed production capstone
- Capstone built in your own BigQuery and dbt Cloud, with human review
- Free, open-source Analytics Engineering Toolkit
- GPT tutor on every lesson and exercise
- Interview-prep questions and worked answers
- Lifetime access · every future update included
- 7-day money-back guarantee
Secure checkout · powered by Stripe
1-on-1 coaching with Eric
Prefer direct feedback on your code, portfolio, and interviews? Private mentorship built around your goal — limited spots, by application.
One connected path from query to reviewed project.
Work through SQL, data modeling, dbt, and data quality with browser practice and worked explanations, then bring those skills together in a human-reviewed capstone.
- 01
Practice the implementation
Run SQL and Python against real fixtures, then compare your result with the expected output and explanation.
- 02
Make modeling decisions
Define grain, relationships, tests, metric rules, and failure handling in guided scenarios and projects.
- 03
Produce inspectable evidence
Build work you can validate, document, and explain instead of relying on a completion claim alone.
- 04
Receive human capstone feedback
Submit the final project for a review of the result, documentation, and technical decisions.
Is this the right learning format for you?
This is a self-paced, practice-led course. Most of your time goes to writing queries, building models, investigating mistakes, and completing a project.
Good fit
You want structured technical practice, realistic projects, and feedback on a completed capstone.
Different needs
You need scheduled live classes, daily instructor availability, or a program focused primarily on Excel and dashboard design.
Experienced learners
Start with the diagnostic so you can move past foundations you already understand.
Course contents by the numbers.
What 1-on-1 tutoring clients say about Eric.
- ★★★★★Mentoring note 01
“Such a great mentor, and so calm and understanding. As a newbie to SQL I found it intimidating, but I appreciate Eric's support throughout. 10/10 would recommend.”
Verified Codementor menteeLearning SQL from scratch - ★★★★★Mentoring note 02
“With only 2 sessions I'm confident I can improve my SQL, Python, and Snowflake skills. Go with Eric — you can't go wrong.”
Verified Codementor menteeSQL · Python · Snowflake - ★★★★★Mentoring note 03
“Walked in terrified of SQL and now I feel ready to learn more. Eric was candid about his experience and shared resources and tips that can help my career.”
Verified Codementor menteeSQL · career advice
Questions worth answering.
Access, pacing, grading, support, and the capstone—answered directly.
I have zero technical background. Is this really for me?
Yes. Start with the diagnostic and it will point you toward the foundations you need. Experienced students should take the same diagnostic and move past basics they can already demonstrate.
What does the full program add?
The program connects a diagnostic-shaped path with 1,604 graded exercises, practice challenges, applied labs, selected portfolio projects, and a human-reviewed capstone. SQL and Python run in your browser and are graded on their output; dbt, modeling, and ETL scenarios are checked against worked explanations.
How long will it take?
Depends on how much time you can give it. 10–15 hours a week typically takes about three months. Moonlighting around a full-time job, expect six. The platform tracks your progress so you can pause and resume without losing place.
What if I get stuck?
The built-in GPT tutor can explain or hint in context. For local repository work, the Analytics Engineering Toolkit is available now for SQL review, dbt health checks, data profiling, and data-quality investigation.
Is my work graded? Is there an instructor?
The course is self-paced. SQL and Python exercises auto-grade in the browser; modeling, dbt, and ETL scenarios are checked against worked explanations. The completed capstone is the one deliverable that receives written human review. For line-by-line review of your code, portfolio, or interview preparation, 1-on-1 coaching is available separately.
Is the content kept up to date?
The curriculum is revised as updates are released, and lifetime access includes those released course revisions. The course page shows the currently published module list.
What if it's not for me?
7-day refund. Try the first three modules, do the exercises, and if it's not delivering value, email and you'll get a full refund.
Will the AI tools section help me in interviews?
Module 9 covers prompt patterns for SQL review, dbt generation, modeling, and using Cursor as a coding partner. It provides concrete examples you can discuss in an interview.