add lp

Author: madiepev

learn-pr/paths/operationalize-gen-ai-apps/index.yml

@@ -0,0 +1,34 @@
+### YamlMime:LearningPath
+uid: learn.wwl.operationalize-gen-ai-apps
+metadata:
+  title: Operationalize generative AI applications (GenAIOps)
+  description: Learn how to develop, evaluate, optimize, and deploy generative AI applications (GenAIOps)
+  ms.date: 03/03/2025
+  author: wwlpublish
+  ms.author: madiepev
+  ms.topic: learning-path
+  ms.collection: wwl-ai-copilot
+  ms.custom: [copilot-learning-hub]
+title: Operationalize generative AI applications (GenAIOps) 
+prerequisites: |
+  Before starting this learning path, you should be familiar with fundamental generative AI concepts and services in Azure. Consider completing the [Microsoft Azure AI Fundamentals: Generative AI](/training/paths/introduction-generative-ai/?azure-portal=true) learning path first.
+summary: |
+  To effectively scale generative Artificial Intelligence (AI) applications, you need to manage, deploy, and maintain GenAI apps to ensure their performance, reliability, and continuous improvement in real-world applications.
+iconUrl: /training/achievements/generic-badge.svg
+levels:
+- intermediate
+roles:
+- data-scientist
+- ai-engineer
+products:
+- ai-services
+subjects:
+- artificial-intelligence
+- machine-learning
+- natural-language-processing
+modules:
+- learn.wwl.plan-prepare-genaiops
+- learn.wwl.ai-foundry-sdk
+- learn.evaluate-generative-ai-apps
+trophy:
+  uid: learn.wwl.create-custom-copilots-ai-studio.trophy

learn-pr/wwl-data-ai/plan-prepare-genaiops/includes/5-tools-frameworks.md

@@ -12,7 +12,7 @@ Once your environment is set up with AZD, the next step in developing AI applica
 
 |Tool|Use|
 |---|---|
-|[AZD AI Template](https://learn.microsoft.com/collections/5pq0uompdgje8d?sharingId=ADFFF9D4AD9A0F29&WT_mc.id=aip-114567-cassieb&azure-portal=true)|A set of prebuilt infrastructure templates that allow you to quickly deploy AI applications in Azure without manually configuring every component. It simplifies the process of setting up resources.|
+|[AZD AI Template](/collections/5pq0uompdgje8d?sharingId=ADFFF9D4AD9A0F29&WT_mc.id=aip-114567-cassieb&azure-portal=true)|A set of prebuilt infrastructure templates that allow you to quickly deploy AI applications in Azure without manually configuring every component. It simplifies the process of setting up resources.|
 |[Chat playground](/azure/ai-studio/quickstarts/get-started-playground?azure-portal=true)|An interactive environment within the Azure AI Foundry portal for testing and refining AI-generated responses. It enables you to experiment with Generative AI models before deploying them to production.|
 
 Now that you have the necessary resources and explored the available language models, you can customize a model to your specific needs.
@@ -55,7 +55,7 @@ When you want to quickly explore prompts, you can use the chat playground in the
 
 |Tool|Use|
 |---|---|
-|[Azure AI Foundry prompt templates](azure/ai-studio/how-to/develop/sdk-overview?branch=main&tabs=sync&pivots=programming-language-python#prompt-templates&azure-portal=true)|A template that allows you to dynamically generate prompts using inputs that are available at runtime, part of the Azure AI Inference SDK.|
+|[Azure AI Foundry prompt templates](/azure/ai-studio/how-to/develop/sdk-overview?branch=main&tabs=sync&pivots=programming-language-python#prompt-templates&azure-portal=true)|A template that allows you to dynamically generate prompts using inputs that are available at runtime, part of the Azure AI Inference SDK.|
 |[Prompty](https://prompty.ai/?azure-portal=true)|A tool to manage prompts, which are the instructions or queries given to the AI model. Prompty helps you track the performance of different prompts and optimize them for better responses.|
 
 When you're experimenting with prompts, you want to evaluate how your model performs. **Evaluators** are either built in or custom insights into your model's performance. Whereas evaluators are based on how a given dataset is processed, you can also include **tracing** to gain more insights into how your application is being executed.