AI-3016: Develop generative AI apps in Azure

Candidates for this training should be familiar with the fundamental concepts and services of AI in Azure. It is recommended to complete the following module before starting the training: Getting Started with Artificial Intelligence.

Plan and prepare for the development of AI solutions on Azure

• Identify common AI features that you can implement in apps
• Describe Azure AI services and considerations for using them.
• Describe Azure AI Foundry and considerations for using it.
• Identify the appropriate development tools and SDKs for an AI project
• Describe responsible AI considerations

Select, deploy, and evaluate Microsoft Foundry models

• Explore and filter templates in the template catalog
• Compare models using benchmark metrics for quality, security, cost, and performance
• Deploy a model to an endpoint and test it in the playground
• Evaluate model performance using manual and automated approaches
• Understand the different evaluation metrics and when to use them

Develop a generative AI conversation app with Microsoft Foundry

• Describe the process of building a generative AI conversation app with Microsoft Foundry.
• Use the conversation playground to explore patterns and generate code samples.
• Choose an endpoint, authentication method, and client SDK for your app development.
• Use the Responses API to generate AI responses in applications.
• Use the ChatCompletions API to generate AI responses in apps.

Develop generative AI applications that use tools

• Describe the functionalities of generative ARTIFICIAL INTELLIGENCE tools.
• Use the code_interpreter tool to run code and analyze data.
• Use the web_search tool to retrieve real-time information from the internet.
• Use the file_search tool to access and analyze files.
• Use the function tool to run custom code.

Optimize generative AI model performance with Microsoft Foundry

• Practice prompt engineering techniques, including system messages, learning in a few examples, and tuning model parameters to optimize the results generated.
• Understand when and how to anchor a language model using augmented recovery generation (RAG).
• Identify when fine-tuning a model improves behavioral consistency.
• Compare optimization strategies and determine when to combine them

Implement a responsible generative AI solution in Microsoft Foundry

• Describe a global process for the development of responsible ARTIFICIAL INTELLIGENCE solutions
• Identify and prioritize potential damage relevant to a generative AI solution
• Measuring the presence of damage in a generative AI solution
• Mitigating the Damage in a Generative AI Solution
• Prepare for the deployment and operation of a generative AI solution responsibly

Published on April 15, 2026

In this training, we mix theory with technical workshops to quickly make you operational. Additionally, each participant receives course materials at the end of the training.

One of our consultant trainers conducts the training. With solid field experience, they make the learning process both interactive and enriching.

For assessment, the trainer regularly asks questions and uses various methods to continuously measure your progress. This approach promotes a dynamic and engaging learning experience.

After the training, we ask you to complete a satisfaction questionnaire. Your feedback helps us to maintain and constantly improve the quality of our training.

Finally, we offer the flexibility to deliver this training both in-person and remotely, and it can be customized to meet your company’s specific needs upon request.

You can register for one of our training courses up to two business days before it starts, if there are still available places and you signed quote.

If you have specific needs related to a disability, please do not hesitate to make a request; we are happy to adjust our services according to the type of disability.