Improving the Dagster learning curve | Dagster Blog

October 11, 20232 minute read

Improving the Dagster learning curve

Erin Cochran
Erin Cochran

Today we are excited to introduce new resources to empower and inspire you, your team, and the stakeholders in your organization.

Jump to the Dagster University announcement ↓ | Jump to the Dagster Open project

As part of our Launch Week events, Erin shares details on Dagster University while Tim Castillo unveils Dagster Open, a large-scale public Dagster project.

In-depth, self-guided learning with Dagster University

Talking with some of our users revealed that while helpful, the tutorial in our documentation doesn’t go far enough in connecting the dots between all of the concepts in Dagster. To address this, we’ve created Dagster University.

The University’s first course, Dagster Essentials, is geared towards creating a solid foundation for Dagster beginners to build on. With detailed explanations, quizzes, and practice problems, this course will help you and your team get to your “Aha!” moment in no time.

Dagster Essentials contains nine lessons, a capstone project, and an extra credit lesson, all of which are only focused on the essential concepts to building in Dagster. Each Dagster Essentials lesson gently introduces a different Dagster concept by using common, non-technical examples before going into more detail. Once completed, you'll receive a completion certificate that you can use to share your achievement!

Don’t just take it from us - the wonderful Dagster users who helped us test drive this course have said that Dagster University addresses what was once a huge gap in Dagster education. For example, check out what early Dagster University grads Erik Mason from Castle Biosciences, Inc. and Jonathan Neo from Canva had to say:

We’re thrilled at Dagster University’s initial reception, and so excited to share this resource with the community.

Dagster Essentials is free and available to everyone - all you need to do is sign up at Once enrolled, you can track your progress and learn at your own pace. Completing the course will earn you a certificate of completion, which you can use to share your achievement with others!

Get inspired with Dagster Open Platform

Learning Dagster isn’t a journey that ends once your first assets are made. There are multiple resources available for you to get started with using Dagster, such as our documentation, quickstarts, and (now) Dagster University. These pieces of content are amazing ways to get started using Dagster properly and shorten the early learning curve of using Dagster at your organization.

In addition to all the resources above to help early on in your Dagster journey, we’re also committed to providing proper guidance and references when you’re months into using Dagster. One of the ways we’ll support you is with Dagster Open Platform.

Dagster Open Platform is a complex and at-scale Dagster project. This project is available as an open-source, public repository for others to reference and use as inspiration. Dagster Open Project applies best practices in data engineering and Dagster to build complex asset-based pipelines.

Also, guess what: this is the Dagster project that runs our own business.We have begun open-sourcing parts of our own data platform, so you can see how the Dagster Labs team uses Dagster itself. We use Dagster’s most up-to-date best practices and APIs to build high-quality data pipelines. You and your team can use this project as an example of what Dagster can do and how best to do it. If you’re running a SaaS business, this also aims to be a reference for how data and analytics can be done.

Check out the project on GitHub.

Other resources

Looking for more? If you’re brand new to data engineering or Python, we have a few other resources that can help get you up to speed:

  • Python for beginners - This series is aimed at helping data engineers, data scientists, data analysts, Machine Learning engineers, or others who are new to Python master the basics.
  • Data engineering glossary - Expand your vocabulary (and knowledge) using this guide to key terms used in data engineering.
  • Dagster Docs - When all else fails, check the docs.

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We're always happy to hear your feedback, so please reach out to us! If you have any questions, ask them in the Dagster community Slack (join here!) or start a Github discussion. If you run into any bugs, let us know with a Github issue. And if you're interested in working with us, check out our open roles!

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