Build AI-powered apps with pre-trained models or create your own machine learning models

Azure AI puts artificial intelligence and machine learning at the fingertips of every developer. Want to build ML models? Choose between visual, automated, and code-first interfaces that simplify machine learning for any experience level. Want to use pre-built models? Infuse computer vision, natural language processing, and decision-making capabilities into your apps with simple API calls.

What should I hack?

Put your skills to the test and apply Azure AI to a new or existing project! We welcome projects of all types, including AI-powered apps or devices, conversational bots, ML models, or something else entirely! Check out the resources tab for tips on getting started, and join our Slack office hours to get your questions answered. We’re excited to see what you build! 

New to AI/machine learning?

We've got your back. Our machine learning quickstarts and sample code will help you start building. Need datasets? Azure Open Datasets offers ML-ready open data

What can I do with Azure AI?


Azure AI 101

Office hours schedule

Get your questions answered by Microsoft experts! Join the Slack channel here to access office hours.

  • Thursday, Aug 1 8-10AM PT
  • Wednesday Aug 21 12-2PM PT
  • Wednesday Sep 4 3-6PM PT

View full rules


$23,000 in prizes

First Place

• $10,000 USD
• 30 minute virtual meeting with Microsoft Azure executives
• Featured on the official Microsoft Azure website and blog
• $1,500 Azure credits

Second Place

• $3,000 USD
• Featured on the official Microsoft Azure website and blog
• $1,500 Azure credits

Third Place

• $2,000 USD
• Featured on the official Microsoft Azure website and blog
• $1,500 Azure credits

Popular Choice Awards (top 5 in public voting) (5)

• $200 Microsoft Store gift card

Participation (First 50 eligible submissions) (50)

• $50 Microsoft Store gift card

Devpost Achievements

Submitting to this hackathon could earn you:


Developers and data scientists of all backgrounds and skill levels are encouraged to submit projects. 

Individuals, and teams of individuals, must have reached the age of majority in their jurisdiction of residence at the time of entry

Note: government officials, corporations, and employees of Microsoft or DevPost are not eligible to win prizes, but may submit projects. See full rules for further restrictions.


Main requirements

Use one or more of following Azure AI services to build a new project or update an existing project: Azure Machine Learning service, Azure Cognitive Services, and Azure Search. Projects may integrate with other Azure services, open source technologies (including but not limited to frameworks, libraries, and APIs) and physical hardware of your choice.

How to enter


  1. Register for the Microsoft Azure AI Hackathon on this page.
  2. Create a free account on Azure. Azure free trial provides $200 credit to explore any service and 12 months of popular free services.
  3. Learn how to use Azure AI services on the resources tab, and check out our machine learning quickstarts and sample code, and ML-ready datasets.
  4. Build! Create a new project that uses Azure AI services or apply them to an existing project. 
  5. Upload your code to Github, making sure to include all deployment files and instructions needed for testing your project. (If the repository is private, share access with Record a video under 5 minutes that demonstrates your project in action.
  6. Submit your project on before September 10th, 2019 @ 2:00pm PT


David Aronchick

David Aronchick
Head of Open Source ML at Microsoft, Creator of Kubeflow

Henk Boelman

Henk Boelman
Founder of Global AI Community

Amy Boyd

Amy Boyd
Cloud Advocate at Microsoft

Nicolo Fusi

Nicolo Fusi
Principal Research Manager, Automated ML team at Microsoft Research

Jennifer Stirrup

Jennifer Stirrup
Award winning data science author

Judging Criteria

  • Quality of the idea
    (Includes creativity and originality of the idea.)
  • Implementation of the Idea
    (Includes how well Azure AI services were leveraged by the developer.)
  • Potential Impact
    (Includes the extent to which the solution can be widely useful.)


  • Machine Learning/ AI