Merge branch 'MicrosoftDocs:main' into main

Author: riswinto

.openpublishing.redirection.json

@@ -4970,7 +4970,7 @@ achievements:
 - uid: learn.chat-completions-badge
   type: badge
   title: Introduction to chat completion
-  summary: This module introduces you to prompt engineering techniques, such as chat completion and system messages, and how to use them in the Azure AI Foundry portal playground.
+  summary: This module introduces you to prompt engineering techniques, such as chat completion and system messages, and how to use them in the Microsoft Foundry portal playground.
   iconUrl: /learn/achievements/generic-badge.svg
 - uid: learn.wwl.examine-iot-hub-message-routing.badge
   type: badge
@@ -5397,8 +5397,8 @@ achievements:
   iconUrl: /training/achievements/generic-trophy.svg
 - uid: learn.wwl.introduction-to-azure-ai-studio.badge
   type: badge
-  title: Introduction to Azure AI Foundry
-  summary: Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Azure AI Foundry brings these services together in a single unified experience for AI development on the Azure cloud platform.
+  title: Introduction to Microsoft Foundry
+  summary: Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Microsoft Foundry brings these services together in a single unified experience for AI development on the Azure cloud platform.
   iconUrl: /learn/achievements/generic-badge.svg
 - uid: learn.wwl.prepare-to-develop-ai-solutions-azure.badge
   type: badge
@@ -6173,7 +6173,7 @@ achievements:
 - uid: learn.intro-generative-ai.trophy
   type: trophy
   title: 'Microsoft Azure AI Fundamentals: Generative AI'
-  summary: "Generative AI is a form of artificial intelligence in which models are trained to generate new original content based on natural language input. In other words, you can describe a desired output in normal everyday language, and the model can respond by creating appropriate text, image, code, and more. \n\nTake this learning path to get started with generative AI. In it, you'll learn how to:\n- Understand core concepts of generative AI\n- Prepare for an AI development project\n- Describe considerations and practices for responsible generative AI\n- Build an AI agent using Azure AI Foundry"
+  summary: "Generative AI is a form of artificial intelligence in which models are trained to generate new original content based on natural language input. In other words, you can describe a desired output in normal everyday language, and the model can respond by creating appropriate text, image, code, and more. \n\nTake this learning path to get started with generative AI. In it, you'll learn how to:\n- Understand core concepts of generative AI\n- Prepare for an AI development project\n- Describe considerations and practices for responsible generative AI\n- Build an AI agent using Microsoft Foundry"
   iconUrl: /learn/achievements/generic-badge.svg
 - uid: learn.advocates.azure-functions-and-signalr.badge
   type: trophy
@@ -6303,7 +6303,7 @@ achievements:
 - uid: learn.wwl.develop-ai-solutions-azure-openai.trophy
   type: trophy
   title: Develop Generative AI solutions with Azure OpenAI in Foundry Models
-  summary: Azure OpenAI in Foundry Models provides access to OpenAI's powerful large language models such as GPT and Embeddings models. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure AI Foundry.
+  summary: Azure OpenAI in Foundry Models provides access to OpenAI's powerful large language models such as GPT and Embeddings models. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Microsoft Foundry.
   iconUrl: /training/achievements/develop-ai-solutions-azure-openai.svg
 - uid: learn.send-messages-rabbitmq-dotnet-aspire-app.badge
   type: badge
@@ -7235,7 +7235,6 @@ achievements:
   title: Foundations of data science for machine learning
   summary: Machine learning is a powerful, modern way to analyze data and make predictions. Using data science fundamentals, you'll learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models.
   iconUrl: /training/achievements/machine-learning/machine-learning-foundations-using-data-science.svg
-
 - uid: learn.machinelearning.optimize-model-performance-roc-auc-dropout.badge
   type: badge
   title: Measure and optimize model performance with ROC and AUC
@@ -7276,4 +7275,118 @@ achievements:
   title: Introduction to machine learning
   summary: A high-level overview of machine learning for people with little or no knowledge of computer science and statistics. You'll learn some essential concepts, explore data, and interactively go through the machine learning lifecycle, using Python to train, save, and use a machine learning model, just like in the real world.
   iconUrl: /training/achievements/machine-learning/introduction-to-machine-learning.svg
-
+- uid: learn.azure.logic-apps-and-custom-connectors.badge
+  type: badge
+  title: Call an API from an Azure Logic Apps workflow using a custom connector
+  summary: Call any Web API from a logic app workflow using the custom connector.
+  iconUrl: /training/achievements/logic-apps-and-custom-connectors.svg
+- uid: learn.azure.intro-to-translator.badge
+  type: badge
+  title: Introduction to Azure AI Translator
+  summary: Azure AI Translator is a cloud-based service that uses AI to reliably translate text and documents between languages in near real time. You can add multilanguage user experiences to your apps in 90 languages and dialects, along with free text translation with any operating system. Translator also has customizable translation models that can better understand industry-specific terminology or pronouns.
+  iconUrl: /training/achievements/intro-to-translator.svg
+- uid: learn.build-serverless-api-with-functions-api-management.badge
+  type: badge
+  title: Expose multiple Azure Function apps as a consistent API by using Azure API Management
+  summary: Combine multiple Azure Functions apps into a unified interface by importing them into a single Azure API Management instance.
+  iconUrl: /training/achievements/build-serverless-api-with-functions-api-management.svg
+- uid: learn.azure.monitor-github-events-with-a-function-triggered-by-a-webhook.badge
+  type: badge
+  title: Monitor GitHub events by using a webhook with Azure Functions
+  summary: Webhooks offer a lightweight mechanism for your app to be notified by another service when something of interest happens. In this module, you'll learn how to trigger an Azure function with a GitHub webhook and parse the payload for insights.
+  iconUrl: /training/achievements/monitor-github-events-with-a-function-triggered-by-a-webhook.svg
+- uid: learn.develop-test-deploy-azure-functions-with-visual-studio.badge
+  type: badge
+  title: Develop, test, and deploy an Azure Function with Visual Studio
+  summary: Create, test, and deploy Azure Functions using Visual Studio and manage Azure Functions code.
+  iconUrl: /training/achievements/develop-test-deploy-azure-functions-with-visual-studio.svg
+- uid: learn.azure-create-long-running-serverless-workflow-with-durable-functions.badge
+  type: badge
+  title: Create a long-running serverless workflow with Durable Functions
+  summary: Learn how to orchestrate a long-running workflow as a set of activities using Durable Functions.
+  iconUrl: /training/achievements/azure-create-long-running-serverless-workflow-with-durable-functions.svg
+- uid: learn.chain-azure-functions-data-using-input-output-bindings.badge
+  type: badge
+  title: Chain Azure Functions together using input and output bindings
+  summary: Azure Functions makes it easy for your function code to integrate with data and services. Through the power of bindings, you declare the data sources to read and write, and let Azure Functions take care of the rest.
+  iconUrl: /training/achievements/chain-azure-functions-data-using-bindings.svg
+- uid: learn.winui-101.badge
+  type: badge
+  title: Build your first Windows App by using WinUI & Windows App SDK
+  summary: Create a Windows app using WinUI 3, Windows App SDK, and Community Toolkit in Visual Studio. Set up the development environment, and build a maintainable, testable, and scalable Windows applications using best practices in software architecture.
+  iconUrl: /training/achievements/winui-101-badge.svg
+- uid: learn.wwl.track-azure-databricks-experiments-azure-machine-learning.badge
+  type: badge
+  title: Track Azure Databricks experiments in Azure Machine Learning
+  summary: Azure Machine Learning is a scalable cloud platform for training, deploying, and managing machine learning solutions.
+  iconUrl: /training/achievements/track-azure-databricks-experiments-in-azure-machine-learning.svg
+- uid: learn.wwl.train-models-scripts-azure-machine-learning.trophy
+  type: trophy
+  title: Train models with scripts in Azure Machine Learning
+  summary: To prepare your machine learning workloads for production, you'll work with scripts. Learn how to train models with scripts in Azure Machine Learning.
+  iconUrl: /training/achievements/train-models-scripts-azure-machine-learning.svg
+- uid: learn.finetune-foundation-model-with-azure-machine-learning.badge
+  type: badge
+  title: Fine-tune a foundation model with Azure Machine Learning
+  summary: Train a pretrained Large Language Model (LLM) on specific tasks. The model catalog in Azure Machine Learning offers many open source models that can be fine-tuned for your specific task.
+  iconUrl: /learn/achievements/generic-badge.svg
+- uid: learn.get-started-prompt-flow.badge
+  type: badge
+  title: Get started with prompt flow to develop Large Language Model (LLM) apps
+  summary: Learn about how to use prompt flow to develop applications that leverage Large Language Models (LLMs).
+  iconUrl: /learn/achievements/generic-badge.svg
+- uid: learn.wwl.deploy-azure-databricks-models-azure-machine-learning.badge
+  type: badge
+  title: Deploy Azure Databricks models in Azure Machine Learning
+  summary: You can use Azure Databricks to train machine learning models, and deploy the trained models in Azure Machine Learning endpoints.
+  iconUrl: /training/achievements/deploy-azure-databricks-models-in-azure-machine-learning.svg
+- uid: learn.dotnet-maui.consume-rest-services.badge
+  type: badge
+  title: Consume REST web services in .NET MAUI apps
+  summary: Build a .NET Multi-platform App UI (MAUI) application that consumes a REST web service by using HttpClient and performs basic CRUD operations. In the app, you detect when your device is connected to the internet to provide a good user experience and take advantage of the native networking stacks to get top performance.
+  iconUrl: /training/achievements/consume-rest-web-services-dotnet-maui-app.svg
+- uid: learn.azure.capture-application-logs-app-service.badge
+  type: badge
+  title: Capture Web Application Logs with App Service Diagnostics Logging
+  summary: Use application logs in Azure Web Apps for debugging web app code.
+  iconUrl: /training/achievements/capture-application-logs-app-service.svg
+- uid: learn.azure.publish-app-with-maven-plugin-for-azure-web-apps.badge
+  type: badge
+  title: Develop Java web app on Azure using Maven
+  summary: Use the Maven plugin for Azure App Service to develop a Java web app and deploy the app to Azure.
+  iconUrl: /training/achievements/publish-app-with-maven-plugin-for-azure-web-apps.svg
+- uid: learn.azure.publish-azure-web-app-with-azure-toolkit-intellij.badge
+  type: badge
+  title: Develop Java web app on Azure using IntelliJ
+  summary: In this module, you'll learn to create a web app in IntelliJ and deploy the app to Azure by using Azure Toolkit for IntelliJ.
+  iconUrl: /training/achievements/publish-a-web-app-to-azure-by-using-azure-toolkit-for-intellij.svg
+- uid: learn.intro-to-azure-data-factory.badge
+  type: badge
+  title: Introduction to Azure Data Factory
+  summary: Microsoft Azure Data Factory is a fully managed, serverless data integration service. It enables you to visually integrate data sources with more than 90 built-in, maintenance-free connectors.
+  iconUrl: /training/achievements/intro-to-azure-data-factory.svg
+- uid: learn.azure.intro-to-azure-ml.badge
+  type: badge
+  title: Introduction to Azure Machine Learning
+  summary: Azure Machine Learning provides an environment to create and manage the end-to-end life cycle of Machine Learning models. Azure Machine Learning's compatibility with open-source frameworks and platforms like PyTorch and TensorFlow makes it an effective all-in-one platform for integrating and handling data and models. Azure Machine Learning is designed for all skill levels, with advanced MLOps features and simple no-code model creation and deployment.
+  iconUrl: /training/achievements/intro-to-azure-ml.svg
+- uid:  learn.azure.ms-learn-live.badge
+  type: badge
+  title: Migrate an ASP.NET Core application from an on-premises environment into Azure
+  summary: You're a senior .NET developer working for a VanArsdel Ltd., a real estate business. VanArsdel has an experienced in-house development team and the technology stack is Microsoft's .NET. Interaction with your customers happens through the website that built with ASP.NET Core MVC and SQL Server and it's hosted on-premises. Management plans to expand the business. The expansion will lead to increased numbers of users hitting the current web application. You conclude the expansion plans require to scale-up hardware to handle increased workload and ensure fast response times. Because of high cost related to these investments, you consider a migration of the solution into the cloud. The positive experience with the Microsoft stack in the past makes you feel comfortable moving to Azure as your cloud provider and you expect a smooth transition. Pushing the application to Azure will help mitigate both, the cost and time factor of upgrading the on-premises solution.
+  iconUrl: /training/achievements/generic-badge.svg
+- uid: learn.microservices-architecture.badge
+  type: badge
+  title: Decompose a Monolithic Application into a Microservices Architecture
+  summary: Improve development agility, deployment, fault tolerance, and scalability by modernizing your application with a microservices architecture.
+  iconUrl: /training/achievements/microservices-architecture.svg
+- uid: learn.github.train-model-debug-with-responsible-ai-dashboard-azure-machine-learning.badge
+  type: badge
+  title: Train a model and debug it with Responsible AI dashboard
+  summary: Learn how to debug an AI model using the Responsible AI dashboard in Azure Machine Learning studio to ensure it performs responsibly and is less harmful.
+  iconUrl: /training/achievements/generic-badge.svg
+- uid: learn.azdo.host-build-agent.badge
+  type: badge
+  title: Host your own build agent in Azure Pipelines
+  summary: Learn how to use your own build agent when Microsoft-hosted agents don't meet your needs.
+  iconUrl: /training/achievements/azure-devops/host-your-own-build-server-in-your-build-pipeline.svg