|
via Udemy |
Go to Course: https://www.udemy.com/course/practice-exams-microsoft-azure-ai-100-azure-ai-engineer/
Certainly! Here's a comprehensive review and recommendation of the Coursera course based on the provided details: --- **Course Review and Recommendation: Azure AI Engineer Certification Preparation on Coursera** **Overview:** This Coursera course is an extensive training program designed to prepare aspiring Azure AI engineers for the Microsoft certification exam. It covers a broad range of topics, from building and managing AI solutions to implementing advanced generative AI models on Azure. The course is tailored for professionals aiming to develop end-to-end AI solutions using Azure AI services, with practical insights into integration, deployment, and management. **Course Content & Structure:** The course is well-structured, aligning with the core skill areas required for the Azure AI Engineer certification: - Planning and managing Azure AI solutions - Implementing content moderation - Developing computer vision, natural language processing, and speech solutions - Knowledge mining, document intelligence, and generative AI It emphasizes hands-on skills such as resource creation, model training, evaluation, deployment, and integration within CI/CD pipelines. Notably, the course includes practice questions that simulate real exam scenarios, complete with explanations and reference links, which are invaluable for exam preparation. **Strengths:** - **Comprehensive Coverage:** The course covers all critical domains such as computer vision, NLP, speech, knowledge mining, and generative AI, making it a one-stop resource for aspiring AI engineers. - **Practical Emphasis:** Focus on real-world implementation, from setting up Azure resources to deploying and monitoring solutions. - **Use of Examples:** The questions, often based on fictitious scenarios, help learners understand application in real-world contexts. - **Up-to-Date Content:** Regular updates ensure the material reflects the latest Azure services and exam requirements. - **Reference Materials:** Detailed explanations and links to official documentation enhance understanding and facilitate independent learning. **Areas for Improvement:** - **Supplementary Material Needed:** While highly detailed, these practice tests should be complemented with other study resources for comprehensive exam readiness. - **Complexity Level:** The advanced nature of content may be challenging for complete beginners; prior experience with Azure and AI concepts is recommended. **Who Should Enroll:** This course is ideal for IT professionals, software developers, data scientists, and cloud engineers aiming for the Azure AI Engineer certification. It is particularly beneficial for those who want a structured, exam-focused course with practical hands-on exercises. **Final Recommendation:** I highly recommend this Coursera course for anyone preparing for the Azure AI Engineer certification. Its extensive curriculum, real-world scenarios, and detailed explanations make it a valuable resource. However, learners should also engage with official Microsoft documentation and additional training materials for a well-rounded preparation strategy. For best results, combine this course with practical experience working on Azure AI projects. --- Feel free to ask if you'd like a more tailored review or additional resources!
In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them.The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time.Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item "B" last time you went through the test.NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material.As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.Your responsibilities include participating in all phases of AI solutions development, including:Requirements definition and designDevelopmentDeploymentIntegrationMaintenancePerformance tuningMonitoringYou work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:Build complete and secure end-to-end AI solutions.Integrate AI capabilities in other applications and solutions.As an Azure AI engineer, you have experience developing solutions that use languages such as:PythonC#You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should:Understand the components that make up the Azure AI portfolio and the available data storage options.Be able to apply responsible AI principles.Skills at a glancePlan and manage an Azure AI solution (15-20%)Implement content moderation solutions (10-15%)Implement computer vision solutions (15-20%)Implement natural language processing solutions (30-35%)Implement knowledge mining and document intelligence solutions (10-15%)Implement generative AI solutions (10-15%)Plan and manage an Azure AI solution (15-20%)Select the appropriate Azure AI serviceSelect the appropriate service for a computer vision solutionSelect the appropriate service for a natural language processing solutionSelect the appropriate service for a speech solutionSelect the appropriate service for a generative AI solutionSelect the appropriate service for a document intelligence solutionSelect the appropriate service for a knowledge mining solutionPlan, create and deploy an Azure AI servicePlan for a solution that meets Responsible AI principlesCreate an Azure AI resourceDetermine a default endpoint for a serviceIntegrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipelinePlan and implement a container deploymentManage, monitor, and secure an Azure AI serviceConfigure diagnostic loggingMonitor an Azure AI resourceManage costs for Azure AI servicesManage account keysProtect account keys by using Azure Key VaultManage authentication for an Azure AI Service resourceManage private communicationsImplement content moderation solutions (10-15%)Create solutions for content deliveryImplement a text moderation solution with Azure AI Content SafetyImplement an image moderation solution with Azure AI Content SafetyImplement computer vision solutions (15-20%)Analyze imagesSelect visual features to meet image processing requirementsDetect objects in images and generate image tagsInclude image analysis features in an image processing requestInterpret image processing responsesExtract text from images using Azure AI VisionConvert handwritten text using Azure AI VisionImplement custom computer vision models by using Azure AI VisionChoose between image classification and object detection modelsLabel imagesTrain a custom image model, including image classification and object detectionEvaluate custom vision model metricsPublish a custom vision modelConsume a custom vision modelAnalyze videosUse Azure AI Video Indexer to extract insights from a video or live streamUse Azure AI Vision Spatial Analysis to detect presence and movement of people in videoImplement natural language processing solutions (30-35%)Analyze text by using Azure AI LanguageExtract key phrasesExtract entitiesDetermine sentiment of textDetect the language used in textDetect personally identifiable information (PII) in textProcess speech by using Azure AI SpeechImplement text-to-speechImplement speech-to-textImprove text-to-speech by using Speech Synthesis Markup Language (SSML)Implement custom speech solutionsImplement intent recognitionImplement keyword recognitionTranslate languageTranslate text and documents by using the Azure AI Translator serviceImplement custom translation, including training, improving, and publishing a custom modelTranslate speech-to-speech by using the Azure AI Speech serviceTranslate speech-to-text by using the Azure AI Speech serviceTranslate to multiple languages simultaneouslyImplement and manage a language understanding model by using Azure AI LanguageCreate intents and add utterancesCreate entitiesTrain, evaluate, deploy, and test a language understanding modelOptimize a language understanding modelConsume a language model from a client applicationBackup and recover language understanding modelsCreate a custom question answering solution by using Azure AI LanguageCreate a custom question answering projectAdd question-and-answer pairs manuallyImport sourcesTrain and test a knowledge basePublish a knowledge baseCreate a multi-turn conversationAdd alternate phrasingAdd chit-chat to a knowledge baseExport a knowledge baseCreate a multi-language question answering solutionImplement knowledge mining and document intelligence solutions (10-15%)Implement an Azure AI Search solutionProvision an Azure AI Search resourceCreate data sourcesCreate an indexDefine a skillsetImplement custom skills and include them in a skillsetCreate and run an indexerQuery an index, including syntax, sorting, filtering, and wildcardsManage Knowledge Store projections, including file, object, and table projectionsImplement an Azure AI Document Intelligence solutionProvision a Document Intelligence resourceUse prebuilt models to extract data from documentsImplement a custom document intelligence modelTrain, test, and publish a custom document intelligence modelCreate a composed document intelligence modelImplement a document intelligence model as a custom Azure AI Search skillImplement generative AI solutions (10-15%)Use Azure OpenAI Service to generate contentProvision an Azure OpenAI Service resourceSelect and deploy an Azure OpenAI modelSubmit prompts to generate natural languageSubmit prompts to generate codeUse the DALL-E model to generate imagesUse Azure OpenAI APIs to submit prompts and receive responsesUse large multimodal models in Azure OpenAIOptimize generative AIConfigure parameters to control generative behaviorApply prompt engineering techniques to improve responsesUse your own data with an Azure OpenAI modelFine-tune an Azure OpenAI model