SQL Server and Azure SQL Labs and Workshops

(https://aka.ms/sqlworkshops)

This site is a map of learning content produced by and curated by the SQL Server and Azure SQL teams in Microsoft Engineering. These materials are meant to be instructor-led, but you can work through the materials on a test system on your own if desired. Labs are shorter and Workshops are more comprehensive. You can view all materials directly in this interface, or you can view the raw github site for this content here.

To download a Workshop or Lab to your local computer, navigate to the Workshop or Lab's github page using the links below. Once there, click the Clone or Download button you see there. More about that process is here.

See the license information at the bottom of this README.md file

Find a problem? Spot a bug? Post an issue here, include the page URL, and we'll try and fix it.

SQL Server Data Platform

• Workshop: SQL Server Ground to Cloud
• Workshop: SQL Server 2019 on OpenShift
• Workshop: SQL Server 2019
• Workshop: SQL Server 2019 Big Data Clusters - Architecture
• Workshop: Kubernetes - From Bare Metal to SQL Server Big Data Clusters
• Lab: SQL Server 2019
• Video Series: Data Exposed

Azure SQL

• Workshop: Azure SQL
• Workshop: SQL Server Ground to Cloud
• Learning Path: Microsoft Learn - Azure SQL Fundamentals
• Lab: Microsoft Azure SQL Labs
• Video Series: Azure SQL Bootcamp
• Video Series: Azure SQL For Beginners
• Video Series: Data Exposed

Programming

• Lab: Python for Data Professionals
• Workshop: R for Data Professionals

Machine Learning and AI

• Workshop: Machine Learning with SQL Server

Presentation Materials, Code, and References

• Presentation Materials - (PowerPoint Decks, etc.)
• Example Code
• References and Tools from the Microsoft SQL Team
• The template for these Workshops and Labs is here - free to use

Learning how to self-learn

Many of these topics are quite deep, and take time to fully absorb. There are several phases of learning:

• Awareness (You learn a technology exists and what it is used for)
• Understanding (You learn the components, processes and steps of a technology)
• Practice (You can perform the steps with the technology by following a process to complete a task)
• Mastery (You are able to explain the technology to others)

If you need a general "Data Literacy" course, you can find that here.

These courses are designed for you to repeat many times to move through these phases. Before you embark on any of these, you may want to complete a "Learning how to Learn" course. You can find more information on that here.

Code of Conduct

This project has adopted the [email protected] with any additional questions or comments.

License

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

Microsoft, Windows, Microsoft Azure and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found at http://go.microsoft.com/fwlink/?LinkID=254653.

Privacy information can be found at https://privacy.microsoft.com/en-us/

Microsoft and any contributors reserve all other rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel or otherwise.

Questions

Email questions to: [email protected]