DP-100 certificate
Hey community! I'm currently preparing the DP-100 certification with a couple of coworkers, two of them already tried a first time and couldn't approve it although they completed the learning path and consistently scored 90+ on the test exam. What they have told me is that the real exam has questions that are a lot harder, and especially, questions that are not really answerable with the materials from the learning path, they say that they saw many deep questions about DevOps and other questions of resources of Azure that are not really a part of Azure Machine Learning or Foundry. I wanted to ask if anyone had a similar experience with this, I thought the exam was centered on the use of azure machine learning (and AI foundry). Can the exam contain questions that are not related with azure machine learning or foundry? Would really appreciate help here! Thanks everyone!
Request to merge multiple Microsoft Learn certification IDs
Hello Microsoft Learn Support Team, I was advised by Pearson VUE and Microsoft Support to contact Microsoft Learn to request merging of my certification profiles. I have paid for the PL-900 exam, but the exam confirmation and status are not visible due to multiple Microsoft Learn IDs. The following Microsoft Learn IDs need to be merged: - ms1100781607 - ms1100998551 - ms1100999029 Kindly help merge these IDs and associate my PL-900 exam correctly. Thank you.Building learning communities: Microsoft MVPs making a difference with Microsoft Learn
Microsoft Learn continues to evolve with the help of our global community of Microsoft MVPs. MVPs build and sustain communities of learning by creating resources, organizing inclusive events, mentoring peers, connecting learners with the right content, and sharing feedback on Learn. Meet a few MVPs whose contributions are making a difference, both locally and globally. Muhammad Samiullah- Developer Technologies and Microsoft Azure MVP Muhammad is a Solution Engineer at Mazik Global and founder of the MLSA Karachi User Group, where he organizes community events in Karachi, Pakistan that connect students and learners with practical Azure skills. Through mentoring, sharing expertise at meetups, or highlighting helpful resources and Learn content, Muhammad helps developers in Pakistan build skills with Microsoft’s cloud technologies. He also shares feedback on Learn platform features like Plans to make them even more accessible and relevant for learners. In Muhammad’s own words: "My inspiration to contribute has always come from two passions: emerging technology and empowering the community. What began with the Microsoft Student Ambassador program has now grown into my journey as a Microsoft Most Valuable Professional, where I continue to share knowledge, create accessible learning experiences, and support students and professionals in their growth. Seeing the real impact of these contributions, whether through Microsoft Learn initiatives, mentorship, or community events, motivates me every day." Jonah Andersson- Microsoft Azure MVP Jonah is a Senior Azure Consultant, author of Learning Microsoft Azure, host of the podcast Extend Women in Tech, and founder of Azure User Group Sweden, where she hosts regular meetups to help developers learn cloud technologies. She’s dedicated to empowering others through mentorship, technical education, and advocacy for diversity in tech. Her inclusive approach and continuous sharing of Azure knowledge (for which she won a Nordic Women in Tech Award) have empowered countless developers in Sweden and beyond to advance their skills. In Jonah’s own words: "As an active learner and community leader, it inspires and motivates me to share what I know to others through tech communities via Microsoft Learn. It is a great platform to learn, collaborate, and connect with like-minded learners who want to upskill and learn as much as they can about AI, Azure, .NET and other Microsoft technologies. My personal mission is to keep learning by doing, by sharing, by teaching, and by inspiring others through the evolving technologies we have today. In my spare time, I’m learning more about AI, Azure AI, MCP servers, and other innovative topics." Kevin Chant- Data Platform MVP, MCT Kevin is a long-time Data Platform community leader. He has been involved in organizing community events, like co-founding a free online conference for the Data Platform community, and sharing practical tips and templates for data professionals on his blog. Kevin exemplifies how MVPs build up the community: he not only offers feedback that improves Learn content and features to support all learners but also creates spaces where people can learn from each other and succeed together. In Kevin’s own words: "I have always loved working with technology. Many people helped me when I first got involved with the Microsoft Data Platform community, as well as other areas. Now, I get to give back and share my knowledge and help steer the direction in many areas. I am passionate about helping others learn, so for me being involved with Microsoft Learn is a natural fit." Jack Lee- Microsoft Azure and Azure AI Foundry MVP Jack is a Senior Azure Certified Consultant, author, and a Cloud Solutions Architect who leads the North Toronto Cloud & DevOps User Group, organizing monthly meetups to help developers and IT pros grow in their careers. He shares Microsoft Learn content and cloud best practices on his blog, and has given talks at community events to spotlight new Azure and AI technologies. An experienced mentor, Jack has a knack for making complex cloud concepts accessible. His efforts have helped many discover helpful training resources on Learn and eased their onboarding into Azure and AI with clearer guidance and community support. In Jack’s own words: "As a community leader and an avid cloud and AI practitioner, I'm passionate about giving back by mentoring others, contributing to community initiatives, and helping peers navigate the ever-changing world of cloud and AI technologies. This is why I always advocate for the Microsoft Learn platform. Microsoft Learn is a dynamic hub which offers the latest official Microsoft documentation, best practices, and hands-on learning paths. Whether I am exploring new Azure services, deepening my understanding of AI frameworks and models, or preparing for certifications, Microsoft Learn helps me build skills that are both cutting-edge and highly relevant." Luke Murray- Microsoft Azure MVP Luke is a Cloud Architect and Microsoft Learn Expert who shares Microsoft Azure knowledge through his blog and local user groups. Based in New Zealand, he organizes community sessions and writes in-depth guides to help fellow professionals make the most of new Microsoft topics (for example, his blog post demystifying the Learn MCP Server). By combining technical insights with a passion for teaching, Luke has helped many IT pros and developers advance their skills via Microsoft Learn. In Luke’s own words: "It’s an honour to be part of such a supportive, collaborative, and inclusive community, where helping just one person can create a ripple effect. I’ve benefited from others’ support in my own journey, and believe that learning, failing, and trying new things (with a hint of stoicism: Ask yourself, “What’s the risk if you don’t?”) is what makes us all better. If you’re passionate about learning and sharing, join the Azure Cloud Commanders learning room for global conversations and opportunities." Continuing the journey together Each of these MVPs brings a unique perspective to Microsoft Learn, but all share a commitment to building stronger, more inclusive communities where everyone can succeed. If you’re an MVP or a community leader, we invite you to share your experiences, get involved in engagement opportunities, and help others discover the benefits of Microsoft Learn. Discover more about the Microsoft MVP program or explore ways to contribute on Microsoft Learn.Model Mondays S2:E4 Understanding AI Developer Experiences with Leo Yao
This week in Model Mondays, we put the spotlight on the AI Toolkit for Visual Studio Code - and explore the tools and workflows that make building generative AI apps and agents easier for developers. Read on for my recap. This post was generated with AI help and human revision & review. To learn more about our motivation and workflows, please refer to this document in our website. About Model Mondays Model Mondays is a weekly series designed to help you grow your Azure AI Foundry Model IQ step by step. Each week includes: 5-Minute Highlights – Quick news and updates about Azure AI models and tools on Monday 15-Minute Spotlight – Deep dive into a key model, protocol, or feature on Monday 30-Minute AMA on Friday – Live Q&A with subject matter experts from the Monday livestream If you're looking to grow your skills with the latest in AI model development, this series is a great place to begin. Useful links: Register for upcoming livestreams Watch past episodes Join the AMA on AI Developer Experiences Visit the Model Mondays forum Spotlight On: AI Developer Experiences 1. What is this topic and why is it important? AI Developer Experiences focus on making the process of building, testing, and deploying AI models as efficient as possible. With the right tools—such as the AI Toolkit and Azure AI Foundry extensions for Visual Studio Code—developers can eliminate unnecessary friction and focus on innovation. This is essential for accelerating the real-world impact of generative AI. 2. What is one key takeaway from the episode? The integration of Azure AI Foundry with Visual Studio Code allows developers to manage models, run experiments, and deploy applications directly from their preferred development environment. This unified workflow enhances productivity and simplifies the AI development lifecycle. 3. How can I get started? Here are a few resources to explore: Install the AI Toolkit for VS Code Explore Azure AI Foundry Documentation Join the Microsoft Tech Community to follow and contribute to discussions 4. What’s New in Azure AI Foundry? Azure AI Foundry continues to evolve to meet developer needs with more power, flexibility, and productivity. Here are some of the latest updates highlighted in this week’s episode: AI Toolkit for Visual Studio Code Now with deeper integration, allowing developers to manage models, run experiments, and deploy applications directly within their editor—streamlining the entire workflow. Prompt Shields Enhanced security capabilities designed to protect generative AI applications from prompt injection and unsafe content, improving reliability in production environments. Model Router A new intelligent routing system that dynamically directs model requests to the most suitable model available—enhancing performance and efficiency at scale. Expanded Model Catalog The catalog now includes more open-source and proprietary models, featuring the latest from Hugging Face, OpenAI, and other leading providers. Improved Documentation and Sample Projects Newly added guides and ready-to-use examples to help developers get started faster, understand workflows, and build confidently. My A-Ha Moment Before watching this episode, setting up an AI development environment always felt like a challenge. There were so many moving parts—configurations, integrations, and dependencies—that it was hard to know where to begin. Seeing the AI Toolkit in action inside Visual Studio Code changed everything for me. It was a realization moment: “That’s it? I can explore models, test prompts, and deploy apps—without ever leaving my editor?” This episode made it clear that building with AI doesn’t have to be complex or intimidating. With the right tools, experimentation becomes faster and far more enjoyable. Now, I’m genuinely excited to build, test, and explore new generative AI solutions because the process finally feels accessible. Coming Up Next Week In the next episode, we’ll be exploring Fine-Tuning and Distillation with Dave Voutila. This session will focus on how to adapt Azure OpenAI models to your unique use cases and apply best practices for efficient knowledge transfer. Register here to reserve your spot and be part of the conversation. Join the Community Building in AI is better when we do it together. That’s why the Azure AI Developer Community exists—to support your journey and provide resources every step of the way. Join the Discord for real-time discussions, events, and peer learning Explore the Forum to catch up on AMAs, ask questions, and connect with other developers About Me I'm Sharda, a Gold Microsoft Learn Student Ambassador passionate about cloud technologies and artificial intelligence. I enjoy learning, building, and helping others grow in tech. Connect with me: LinkedIn GitHub Dev.to Microsoft Tech CommunityDemystifying Azure AI Foundry: A Beginner's Guide
Are you ready to dive into the transformative world of Artificial Intelligence but unsure where to start? You landed at the right page. Welcome! Whether you’re just getting started or have a bit of experience under your belt, this read will provide you with the foundational knowledge needed to unlock the potential of Azure AI Foundry. Azure AI Foundry offers a powerful suite of tools and Machine Learning Models. Let’s start harnessing its capabilities as an initial step to create innovative AI solutions that can revolutionize your projects or business. As a Microsoft Technical Trainer, delivering classes on AI and Data for the past several years, I have witnessed the significant impact AI has had across various industries. My objective here is to equip you with the foundational knowledge and confidence necessary to embark on your AI journey. Azure AI Foundry (formerly Azure AI Studio) is a suite of tools that makes artificial intelligence accessible to everyone. It allows users to build, deploy, and manage AI solutions easily. Azure AI Foundry can be leveraged to address real-world business challenges and foster innovation. For instance, Azure AI Foundry can enhance predictive maintenance in manufacturing by analyzing sensor data to foresee equipment failures to minimize downtime and costs. In retail, it can perform customer sentiment analysis across social media, reviews, and surveys, offering insights into customer satisfaction and areas for improvement. For more ways that Azure AI Foundry can help your organization, see customer stories here: Azure AI Foundry - Generative AI Development Hub and here: Need inspirations? Real AI Apps stories by Azure customers to help you get started With Azure AI Foundry, you can explore and develop various AI models and services tailored to your goals. The platform supports scalability, enabling proof of concepts to become full production applications effortlessly. It also has support for continuous monitoring and refinement ensuring long-term success. Here's a brief overview of AI Foundry's main architectural components and their integration. Azure AI Foundry architecture - Azure AI Foundry At the top level, AI Foundry provides access to the following resources: Management Center: Used to manage AI Foundry resources like hubs, projects, connected resources, and deployments. It is a part of the Azure AI Foundry portal that streamlines governance and management activities. In the management center, you can view and manage: Projects and resources Quotas and usage metrics Govern access and permissions For more information see: Management center overview - Azure AI Foundry AI Foundry Hub: The main top-level resource in the AI Foundry portal, offering a centralized method for managing security, connectivity, and computing resources across playgrounds and projects. Once a hub is established, developers can create projects from it and access shared resources like storage accounts, key vaults, databases and others without requiring continuous assistance from an IT administrator. The hub uses the Azure Machine Learning service and this Azure Provider, Microsoft.MachineLearningServices/workspaces and the type is hub. It offers: Security features, including a managed network for projects and model endpoints. Computer resources for development, fine-tuning, open-source, and serverless model deployments. Connections to other Azure services, such as Azure OpenAI and Azure AI Search. An Azure storage account for data and artifacts. AI Foundry Project: A project is part of the hub. Projects help organize work, save state across tools like prompt flow and enable collaboration. You can share files and data source connections within a project. Hubs support multiple projects and users. Projects manage billing, access, and provide data isolation, using dedicated storage containers to securely share files among project members. Once you have a project, you can connect to it from your code. You can explore models and capabilities before creating a project, but once you're ready to build, customize, test, and operationalize, a project is where you'll want to be. The Azure provider for a project is Microsoft.MachineLearningServices/workspaces, and the type is Project. The project offers: Reusable assets like datasets, models, and indexes. A container for uploading data within the hub's storage. Private data access for project members. Model deployments from the catalog and adjusted model endpoints. Connections: AI Foundry hubs and projects use connections to access resources from other services, such as an Azure Storage Account, Azure OpenAI, or other Azure AI services. Once you have setup the Azure Foundry Hub, Project and Connection, its time to start exploring and deploying the models. Model Catalog: Available in Azure AI Foundry portal to discover and use a wide range of models for building generative AI applications. The model catalog features hundreds of models across model providers such as Azure OpenAI Service, Meta, NVIDIA, Hugging Face, DeepSeek, and of course the models trained by Microsoft like Phi. Azure AI Model Catalog – Foundation Models You can search and discover models that meet your needs. The model catalog also offers the model performance benchmark metrics which can be accessed by using Compare Models feature or from the model card Benchmark tab. Models need to be deployed to make them available for receiving inference requests. Azure AI Foundry offers a comprehensive suite of deployment options for those models depending on your needs and model requirements. Prompt Flow: This feature can be used to generate, customize, or run a flow. A flow is an executable instruction set that can implement the AI logic. Flows can be created or run via multiple tools, like a prebuilt canvas, LangChain, etc. Iterations of a flow can be saved as assets; once deployed a flow becomes an API. Prompt flow in Azure AI Foundry portal - Azure AI Foundry A prompt is sent to a model, consisting of the user input, system message, and any examples. User input is text submitted in the chat window. System message is a set of instructions to the model scoping its behaviors and functionality. Evaluators: Helpful tools to assess the frequency and severity of content risks or undesirable behavior in AI responses. Performing iterative, systematic evaluations with the right evaluators can help teams measure and address potential response quality, safety, or security concerns throughout the AI development lifecycle. You can explore Azure AI Foundry benchmarks to evaluate and compare models on publicly available datasets. Deploy: Remember to deploy your model setup. Deployments are hosted within an endpoint and can receive data from clients and send responses back in real-time. You can invoke the endpoint for real-time inference for chat, copilot or another generative AI application. AI Foundry has all the needed capabilities including content filters, Responsible AI factors and Security. More about these aspects in my next article. Playgrounds: Be sure to test your model using the Playgrounds on Azure AI Foundry. The portal offers a chat playground for deploying and interacting with AI chat models, allowing you to refine them before production deployment. Hear and speak with chat models in the Azure AI Foundry portal chat playground - Azure AI Foundry Now that you have the foundational knowledge, I encourage you to begin using Azure AI Foundry by following the resources and guidelines provided. Ready to get started with Azure AI Foundry? Here are some tutorials to guide you: Use the chat playground in Azure AI Foundry portal Tutorial: Deploy an enterprise chat web app in the Azure AI Foundry portal playground Explore, learn, and transform your ideas into reality with Azure AI Foundry. Stay tuned for more! Happy Learning!
Msn partner hub program Invitation code inquiry
Hi , I don't have access to any publisher of msn partner hub program. But I just wanted to join it at any cost. This is very important for me join it. Please send me an invite code for it. So, I can join it. Or send me the link of any publisher so I can contact him. Please help me out to join this program. It is very essential for life fulfill my life purpose. I will thankful to you. With my best RegardsAZ-500: Microsoft Azure Security Technologies Study Guide
The AZ-500 certification provides professionals with the skills and knowledge needed to secure Azure infrastructure, services, and data. The exam covers identity and access management, data protection, platform security, and governance in Azure. Learners can prepare for the exam with Microsoft's self-paced curriculum, instructor-led course, and documentation. The certification measures the learner’s knowledge of managing, monitoring, and implementing security for resources in Azure, multi-cloud, and hybrid environments. Azure Firewall, Key Vault, and Azure Active Directory are some of the topics covered in the exam.All-in-One Content Creation with the New Microsoft 365 Dashboard
🎨 Discover the new Microsoft 365 Dashboard creation experience! In this video, I’ll walk you through the redesigned interface that makes it easier than ever to create and manage content—whether it’s images, posters, documents, videos, and more. Microsoft is transforming M365 into a true creative hub, perfect for both personal productivity and professional branding. ✅ Learn how to navigate the new dashboard ✅ Explore templates for visuals, documents, and multimedia ✅ See how AI and design tools integrate into your workflow ✅ Tips to boost your productivity with Microsoft 365 💬 Don’t forget to like, subscribe, and share your thoughts in the comments! 📌 Perfect for creators, marketers, educators, and business users. #Microsoft365 #ContentCreation #ProductivityTools #MicrosoftDashboard #M365Tips #Office365 #WorkSmarter #MicrosoftTemplates #DigitalCreativity #CreateWithMicrosoft
