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Exam DP-203: Data Engineering on Microsoft Azure Crash Course

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Table of Contents

About

This instructor-led training course prepares you to clear Exam DP-203: Data Engineering on Microsoft Azure. Exam DP-203 is the prerequisite to earn Microsoft's Azure Data Engineer Associate certification.

Built With

  • Microsoft PowerPoint
  • Techsmith Snagit
  • Microsoft Visual Studio Code
  • Microsoft Azure
  • Azure PowerShell
  • Azure CLI
  • Transact-SQL

Roadmap

See the open issues for a list of proposed features (and known issues).

Support

Reach out to the maintainer at one of the following places:

Project assistance

If you want to say thank you or/and support active development of Exam DP-203: Data Engineering on Microsoft Azure Crash Course:

  • Add a GitHub Star to the project.
  • Tweet about the Exam DP-203: Data Engineering on Microsoft Azure Crash Course on your Twitter.
  • Write interesting articles about the project on Dev.to, Medium or personal blog.

Together, we can make Exam DP-203: Data Engineering on Microsoft Azure Crash Course better!

Contributing

First off, thanks for taking the time to contribute! Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make will benefit everybody else and are greatly appreciated.

We have set up a separate document containing our contribution guidelines.

Thank you for being involved!

Authors & contributors

The original setup of this repository is by Tim Warner.

For a full list of all authors and contributors, check the contributors page.

Security

Exam DP-203: Data Engineering on Microsoft Azure Crash Course follows good practices of security, but 100% security can't be granted in software. Exam DP-203: Data Engineering on Microsoft Azure Crash Course is provided "as is" without any warranty. Use at your own risk.

For more info, please refer to the security policy.

License

This project is licensed under the MIT license.

See LICENSE for more information.

Acknowledgements

Thanks to my Pearson editor Laura Lewin for making this course possible. Thanks to Lindsay Ventimiglia and the rest of the O'Reilly team for your awesome hosting skills. Thanks to all my students, past and present - I appreciate each and every one of you.

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  • Jupyter Notebook 95.3%
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