Course Overview
This course teaches dbt (data build tool) by having you build one project from start to finish: an analytics pipeline on Airbnb-style data. You don't work through isolated feature demos. You see which dbt feature fits which stage of a real project, and why.
It starts with a theory block on where dbt sits in a modern data stack. That block covers ELT versus ETL, warehouses, lakes and lakehouses, and how analytics engineering differs from traditional data engineering. After that, the course moves into hands-on work and finishes with certification preparation. The instructor says the content tracks the current dbt Analytics Engineering exam, and it was last updated in September 2026.
What You Will Learn
- Set up a working dbt environment on Mac or Windows, including a virtual environment, a warehouse connection to Snowflake, a dbt profile, and VS Code extensions.
- Build and organize models, choose between materialization types, and work with sources, seeds, and snapshots.
- Write generic and singular tests, unit tests, and custom tests, and use data contracts.
- Use Jinja, macros, hooks, operations, and community packages to cut repetition.
- Generate and customize documentation, and trace dependencies between transformation steps.
- Apply more advanced features: Python models, constraints, selectors, microbatching, model versioning and deprecation.
- Add extra data quality checks with dbt-expectations.
- Move toward production with orchestration ideas, slim CI, defer, and pull request workflows.
- Work with both dbt Core and dbt Fusion.
- Review exam-style questions in a certification prep section.
Course Structure
The 34 sections fall into three rough blocks:
- Theory: data maturity, architectures, SCDs, CTEs, and the case for dbt.
- Practical build: environment setup, then the Airbnb project, which introduces features in the order a team would actually need them.
- Wrap-up: best practices, a certification guide with a sample test, and recorded conversations with industry practitioners.
If you are short on time, the instructor says the basic and intermediate material is packed into the first three to four hours.
Who Is This Course For?
It suits analysts, BI developers, data scientists, and data engineers who already write SQL and want to move their transformation work into a tested, version-controlled dbt workflow. It also works for people aiming at the dbt certification who want a structured route to the exam topics.
Look elsewhere if you have never written SQL, since the course expects some comfort with queries. It is also a poor match if you already run dbt in production and only want deep dives on one advanced area. The introductory theory and setup would feel slow, and the course covers breadth more than depth.
Format & Time Commitment
Everything is self-paced video, with some assignments, a practice test, articles, and two downloadable resources. You can watch on mobile or TV, and closed captions are available. The video runs a little over 13 hours. If you code along and build the whole project, expect to spend noticeably longer. The instructor stresses finishing the entire Airbnb build rather than skipping steps.
Pros and Cons
Pros
- One continuous project ties the features together, so you see how pieces connect.
- Coverage is broad, from setup through testing, docs, packages, and production workflow.
- It includes both dbt Core and dbt Fusion.
- Exam preparation is built in, with a sample test.
- Reviewers mention the clear explanations and the practitioner interviews.
- Large learner base and regular updates.
Cons
- It uses a single sample domain. Skills transfer, but you won't see how dbt handles very different data models or very large production setups.
- You need a Snowflake connection, plus Git, Python, and GitHub, before you can follow along. Setup can take a while for newcomers.
- At about 13 hours, some advanced topics (CI, orchestration, Python models) get an introduction rather than a deep treatment.
- The certificate is a Udemy completion certificate. It does not replace the official dbt exam, and finishing the course does not guarantee a pass. One reviewer reported failing the first attempt.
- The course is video-led with no live mentoring, so help comes through Q&A rather than direct feedback on your work.
FAQ
Do I need to know SQL first?
Yes. Basic SQL is a stated requirement, and the course builds on it rather than teaching it from nothing.
Will this prepare me for the dbt certification?
It covers the exam topics and includes a practice test. You will likely still want extra practice with dbt's official documentation and hands-on repetition.
Does the certificate carry weight with employers?
It is a completion record from Udemy. Employers tend to value the project you build and any official dbt certification more.
What else could I consider?
Udemy lists related options such as a dbt certification-focused course, a combined Snowflake and dbt course, and a dbt on Databricks course. These are worth a look if your warehouse is different or you want a narrower exam focus.
If the Airbnb project approach fits how you learn, you can read the full curriculum on the official Udemy page.
