{"id":89427,"date":"2023-06-20T06:15:29","date_gmt":"2023-06-20T11:45:29","guid":{"rendered":"https:\/\/www.whizlabs.com\/blog\/?p=89427"},"modified":"2024-04-10T15:32:53","modified_gmt":"2024-04-10T10:02:53","slug":"microsoft-azure-fundamentals-hands-on-labs","status":"publish","type":"post","link":"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/","title":{"rendered":"Best Hands-on Labs for AI-900: Microsoft Azure Fundamentals"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">AI-900: Microsoft Azure Fundamentals is an essential certification offered by Microsoft, designed to equip learners with the fundamental knowledge and skills required to explore the potential of AI on the Azure platform. While theoretical understanding is essential, hands-on experience is invaluable in truly grasping the concepts and gaining practical expertise.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To ensure you make the most of your learning journey, we have compiled a list of the best hands on labs for <\/span><a href=\"https:\/\/www.whizlabs.com\/microsoft-azure-certification-ai-900\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">AI-900: Microsoft Azure Fundamentals<\/span><\/a><span style=\"font-weight: 400;\">. These labs will enable you to put theory into practice, helping you deepen your understanding and develop proficiency in applying AI technologies in Azure.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this article, we will highlight a selection of hands-on labs that cover key topics related to AI-900: <a href=\"https:\/\/www.whizlabs.com\/microsoft-azure-certification-training-courses\/\">Microsoft Azure Fundamentals<\/a>. Whether you are a beginner eager to explore the foundations of AI or an IT professional looking to enhance your Azure skills, these labs will provide you with an immersive and interactive learning experience.<\/span><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_76 ez-toc-wrap-left counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #ea7e02;color:#ea7e02\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #ea7e02;color:#ea7e02\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/#All_about_AI-900_Microsoft_Azure_Fundamentals_Certification\" >All about AI-900: Microsoft Azure Fundamentals Certification<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/#Exam_Format_Image_for_AI-900_Microsoft_Azure_Fundamentals_Certification\" >Exam Format Image for AI-900: Microsoft Azure Fundamentals Certification<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/#Pre-requisites_for_taking_AI-900_Microsoft_Azure_AI_Fundamentals_certification\" >Pre-requisites for taking AI-900: Microsoft Azure AI Fundamentals certification<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/#Top_15_Hands-on_Labs_for_AI-900_Microsoft_Azure_Fundamentals\" >Top 15 Hands-on Labs for AI-900:\u00a0 Microsoft Azure Fundamentals\u00a0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.whizlabs.com\/blog\/microsoft-azure-fundamentals-hands-on-labs\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"All_about_AI-900_Microsoft_Azure_Fundamentals_Certification\"><\/span><span style=\"font-weight: 400;\">All about AI-900: Microsoft Azure Fundamentals Certification<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/learn.microsoft.com\/en-us\/certifications\/exams\/ai-900\/\" target=\"_blank\" rel=\"nofollow noopener\"><span style=\"font-weight: 400;\">AI 900 certification<\/span><\/a><span style=\"font-weight: 400;\"> is a beginner-level certification for data scientists and it can help to become familiar with AI and Machine Learning concepts. Also, it also makes an individual get certified for using Azure services relevant to <a href=\"https:\/\/www.whizlabs.com\/blog\/latest-trends-in-ai-and-ml\/\" target=\"_blank\" rel=\"noopener\">ML and AI<\/a>. In addition, the AI 900: Microsoft Azure AI Fundamentals certification exam can also be used as an effective way for demonstrating key skills and understanding of ML and AI workloads.<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Exam_Format_Image_for_AI-900_Microsoft_Azure_Fundamentals_Certification\"><\/span><span style=\"font-weight: 400;\">Exam Format Image for AI-900: Microsoft Azure Fundamentals Certification<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-85347\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details.webp\" alt=\"AI-900 exam\" width=\"900\" height=\"500\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details.webp 900w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-300x167.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-768x427.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-756x420.webp 756w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-640x356.webp 640w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-681x378.webp 681w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2022\/07\/microsoft-azure-ai-900-certification-exam-details-150x83.webp 150w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Pre-requisites_for_taking_AI-900_Microsoft_Azure_AI_Fundamentals_certification\"><\/span><span style=\"font-weight: 400;\">Pre-requisites for taking AI-900: Microsoft Azure AI Fundamentals certification<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">While making a journey into the world of artificial intelligence (AI) and cloud computing is an exciting prospect. To make the most of your exploration and maximize your understanding of AI-900: Microsoft Azure AI Fundamentals, Microsoft suggests a set of recommended skills that will help you navigate the concepts and principles more smoothly. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">While these skills are not mandatory prerequisites, acquiring them beforehand can enhance your learning experience and enable you to grasp the concepts more effectively.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">General programming knowledge\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Basic working experience with Azure<\/span><\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Top_15_Hands-on_Labs_for_AI-900_Microsoft_Azure_Fundamentals\"><\/span><span style=\"font-weight: 400;\">Top 15 Hands-on Labs for AI-900:\u00a0 Microsoft Azure Fundamentals\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">In the pursuit of mastering AI-900: Microsoft Azure Fundamentals, hands-on labs are an indispensable tool to solidify your knowledge and gain practical experience. These labs offer an immersive and interactive learning environment where you can apply theoretical concepts to real-world scenarios, deepening your understanding of AI on the Azure platform.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">From creating intelligent chatbots to exploring computer vision and predictive analytics, these labs cover a wide range of AI topics, providing you with the opportunity to sharpen your skills and become proficient in leveraging Azure&#8217;s AI capabilities.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here are some top hands-on labs to makes you prepare for AI-900: Microsoft Azure Fundamentals certification are:<\/span><\/p>\n<ul>\n<li><a href=\"https:\/\/www.whizlabs.com\/labs\/create-a-cognitive-services-resource-using-an-arm-template\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Creation of a Cognitive Services resource with the help of an ARM template<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this hands-on lab, you walk through the process of creating a Cognitive Services resource using an <a href=\"https:\/\/www.whizlabs.com\/blog\/azure-resource-manager-template-overview\/\" target=\"_blank\" rel=\"noopener\">Azure Resource Manager (ARM) template<\/a>.<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89645\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive.webp\" alt=\"cognitive\" width=\"827\" height=\"459\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive.webp 827w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-300x167.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-768x426.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-150x83.webp 150w\" sizes=\"(max-width: 827px) 100vw, 827px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">To do so, the following tasks will be carried out such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Need to sign in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Then you need to navigate the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Followed by the deployment of the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Verification of deployment<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/create-an-ubuntu-data-science-virtual-machine-using-an-arm-template\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Creating an ARM template based Ubuntu Data Science Virtual Machine\u00a0<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Throughout this lab, you will learn how to provision an Ubuntu DSVM using the flexibility and scalability of ARM templates.\u00a0<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89644\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/ubuntu.webp\" alt=\"ubuntu\" width=\"808\" height=\"474\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/ubuntu.webp 808w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/ubuntu-300x176.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/ubuntu-768x451.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/ubuntu-150x88.webp 150w\" sizes=\"(max-width: 808px) 100vw, 808px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">To create Ubuntu data science virtual machine, the following tasks are carried out:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Have to sign in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Navigate the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Followed by the deployment of the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Verification of deployment<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/explore-computer-vision\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Navigating Computer Vision<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Through this lab exercise, you will gain practical experience in leveraging the Computer Vision service to extract valuable insights from images with the usage of simple command-line applications.<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89643\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/Computervision.webp\" alt=\"Computervision\" width=\"825\" height=\"394\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/Computervision.webp 825w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/Computervision-300x143.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/Computervision-768x367.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/Computervision-150x72.webp 150w\" sizes=\"(max-width: 825px) 100vw, 825px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">To navigate computer vision, you have to stick to the following steps:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Register via Azure Portal.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Building Cognitive Services resources<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Executing Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Setup and run a client application<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/deploy-cognitive-search-using-bicep\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Deployment of Cognitive Search with the help of Bicep<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will have the opportunity to leverage the power of Bicep to deploy an Azure Cognitive Search resource, enabling you to harness the search capabilities in your applications.<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89630\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep.webp\" alt=\"cognitive search bicep\" width=\"1072\" height=\"630\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep.webp 1072w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep-300x176.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep-1024x602.webp 1024w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep-768x451.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/cognitive-search-bicep-150x88.webp 150w\" sizes=\"(max-width: 1072px) 100vw, 1072px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Some of the tasks performed in this lab such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Need to sign in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Then you need to navigate the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Followed by the deployment of the ARM template<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Verification of deployment<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/exploring-custom-question-answering\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Investigating customized question answering<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this hands-on lab, we will guide you through the process of creating, training, and publishing a bot capable of answering user queries via various interfaces such as a website chat window, email, or voice interface.\u00a0<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89631\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering.webp\" alt=\"custom question answering\" width=\"1076\" height=\"562\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering.webp 1076w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering-300x157.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering-1024x535.webp 1024w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering-768x401.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/custom-question-answering-150x78.webp 150w\" sizes=\"(max-width: 1076px) 100vw, 1076px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Tasks involved such:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Signing in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of a customized knowledge-based question and answering\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Addition of question-and-answer sets to the knowledge base<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Training and testing the knowledge base<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of a bot for a knowledge base<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/exploring-form-recognition\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Investigating Form Recognition<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will have the opportunity to explore the Form Recognizer service by utilizing a command-line application. Through this exercise, you will gain practical experience in leveraging the Form Recognizer service to extract valuable data from forms. Let&#8217;s dive in and uncover the potential of the Form Recognizer service in this interactive lab.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">And tasks involved in these hands-on labs such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Signing in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Cognitive Services resource creation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Configuring and running a client application<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00a0<\/span><a href=\"https:\/\/www.whizlabs.com\/labs\/add-a-dataset-to-your-pipeline-in-azure-machine-learning-studio\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Dataset addition into the pipeline in the Azure Machine Learning Studio<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this hands-on lab, you will learn how to append the data into the pipeline in the <a href=\"https:\/\/www.whizlabs.com\/labs\/azure-machine-learning-studio\" target=\"_blank\" rel=\"noopener\">Microsoft Azure Machine Learning Studio<\/a>.\u00a0<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-89633\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio.webp\" alt=\"azure machine learning studio\" width=\"1076\" height=\"529\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio.webp 1076w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio-300x147.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio-1024x503.webp 1024w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio-768x378.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/azure-machine-learning-studio-150x74.webp 150w\" sizes=\"(max-width: 1076px) 100vw, 1076px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The tasks that can be performed in these hands-on labs such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Signing in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Workspace creation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Compute cluster formation<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of pipeline in Designer<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of dataset<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Loading the data<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/exploring-optical-character-recognition\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Exploration of Optical Character Recognition<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will explore the Read API by using a command-line application. Through this exercise, you will gain practical experience in utilizing the Read API to extract valuable text and data from images.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><img decoding=\"async\" class=\"alignnone size-full wp-image-89636\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/optical-character.webp\" alt=\"optical character\" width=\"798\" height=\"505\" srcset=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/optical-character.webp 798w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/optical-character-300x190.webp 300w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/optical-character-768x486.webp 768w, https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2023\/06\/optical-character-150x95.webp 150w\" sizes=\"(max-width: 798px) 100vw, 798px\" \/><\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tasks performed in this lab include:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Signing in to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Computer Vision resource<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00a0Configuring and running the client application<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/exploring-face-detection\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Navigating Face detection<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will have the opportunity to explore the Face service by using a command-line application. And you will gain practical experience in utilizing the Face service to analyze and extract valuable insights from the facial data.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To successfully carry out the tasks in these hands-on labs, follow below steps:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Visit the Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Select Face API resource<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Run the Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Configuring and running a client application<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/object-detection-using-custom-vision-service\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Object detection with the help of Custom Vision Service<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will have the opportunity to explore the Custom Vision service and its object detection capabilities by using a command-line application. And you will know how to utilize the Custom Vision service to detect objects in images.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tasks carried out in these hands-on labs such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Login into Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Custom Vision project<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding and Tagging the images<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Training and testing a model<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Publishing the object detection model<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Configuring and running applications of the client<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/understanding-clustering-with-azure-machine-learning-designer\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Clustering with the usage of Azure Machine Learning designer<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, we will work with a dataset containing penguin measurements and species labels. You will learn how to preprocess the data, create a clustering model, and evaluate its performance.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By the end of this lab, you will have gained practical experience in building a clustering model that can identify penguin species based on their attributes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this lab, the following steps will be made:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Azure Machine Learning workspace<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of computing cluster<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Building pipeline in designer<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dataset creation from the web files<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Loading the data to Canvas and appending transformations to it<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transformed data\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding the training modules<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the training pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding and evaluating the Model module<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creating inference pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Service deployment<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Testing the service<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/create-a-pipeline-in-azure-machine-learning-studio\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Pipeline creation in Azure Machine Learning Studio<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will have the opportunity to create a machine-learning workspace, which serves as the central hub for your machine-learning projects. Additionally, you will explore the Azure Machine Learning Studio designer, a visual interface that allows you to easily construct and execute machine learning pipelines.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tasks included in this hands-on lab such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access to the Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of workspace<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of compute cluster<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pipeline creation in Designer<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/train-a-model-in-azure-machine-learning-studio\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Training a model in the\u00a0 Azure Machine Learning Studio<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will be introduced to the process of training a model using Azure Machine Learning Studio.<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Azure Machine Learning workspace<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of computing cluster<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Building pipeline in designer<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dataset creation from the web files<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Loading the data to Canvas and appending transformations to it<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transformed data\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding the training modules<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the training pipeline<\/span><\/li>\n<\/ol>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><a href=\"https:\/\/www.whizlabs.com\/labs\/deploy-and-test-the-model\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Deploying and testing the model<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">This lab will teach you the process of evaluating, deploying, and testing a model within Azure Machine Learning Studio.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u00a0By following the instructions, you will gain hands-on experience in assessing model performance, deploying models for practical use, and conducting rigorous testing to ensure their effectiveness.<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Azure Machine Learning workspace<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of computing cluster<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Building pipeline in designer<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dataset creation from the web files<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Loading the data to Canvas and appending transformations to it<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transformed data\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding the training modules<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the training pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding and evaluating the Model module<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creating inference pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Service deployment<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Testing the service<\/span><\/li>\n<\/ol>\n<ul>\n<li><a href=\"https:\/\/www.whizlabs.com\/labs\/analyze-text-with-text-analytics-on-azure\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Analyzing the Text with Text Analytics on Azure<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, you will explore and experiment with the text analytics capabilities offered by the Language service within Azure Cognitive Services.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By engaging in this lab, you will gain practical knowledge on how to test and leverage the various text analytics features provided by Azure Cognitive Services for tasks such as sentiment analysis, keyphrase extraction, and language detection.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tasks performed in this lab such as:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Login to Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Create a Cognitive Services resource<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Execute\u00a0 Cloud Shell<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Configuring and running the client application<\/span><\/li>\n<\/ol>\n<ul>\n<li><a href=\"https:\/\/www.whizlabs.com\/labs\/understanding-classification-with-azure-machine-learning-designer\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Classification with Azure Machine Learning designer<\/span><\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In this lab, we will guide you through the process of creating a classification model that predicts the likelihood of a patient contracting diabetes. The model will be built using various factors or features related to the patient&#8217;s health.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By following the steps outlined in this lab, you will gain hands-on experience in constructing a predictive model for diabetes using machine learning techniques.<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access Azure Portal<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of Azure Machine Learning workspace<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creation of computing cluster<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Building pipeline in designer<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dataset creation from the web files<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Loading the data to Canvas and appending transformations to it<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transformed data\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding the training modules<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Running the training pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Adding and evaluating the Model module<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Creating inference pipeline<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Service deployment<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Testing the service<\/span><\/li>\n<\/ol>\n<div class=\"ast-oembed-container \" style=\"height: 100%;\"><iframe title=\"Fairness in an AI solution | AI-900 | Whizlabs\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/9hgNioGrGc8?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><span style=\"font-weight: 400;\">Conclusion<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">By participating in AI-900 hands-on labs, you will learn how to use Azure Cognitive Services to build intelligent applications, gain insights from data using Azure Machine Learning, and understand the fundamentals of AI ethics and responsible AI practices.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The hands-on labs provide step-by-step instructions, interactive exercises, and real-world scenarios to enhance your understanding and proficiency in leveraging AI technologies on the Azure platform.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Overall, the hands-on labs for AI-900: Microsoft Azure Fundamentals are a valuable resource for beginners or professionals who want to kickstart their journey into AI and gain a solid foundation in Azure AI services. Through practical exercises, you can develop the skills and knowledge necessary to leverage AI effectively and make informed decisions in your future AI projects on the Microsoft Azure platform.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you have any comments or questions on this blog post, please contact us today!<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI-900: Microsoft Azure Fundamentals is an essential certification offered by Microsoft, designed to equip learners with the fundamental knowledge and skills required to explore the potential of AI on the Azure platform. While theoretical understanding is essential, hands-on experience is invaluable in truly grasping the concepts and gaining practical expertise. To ensure you make the most of your learning journey, we have compiled a list of the best hands on labs for AI-900: Microsoft Azure Fundamentals. These labs will enable you to put theory into practice, helping you deepen your understanding and develop proficiency in applying AI technologies in Azure. [&hellip;]<\/p>\n","protected":false},"author":13,"featured_media":89596,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"default","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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