Cours AI-900 Fondamentaux de l'IA Azure avec Simulations Virtuelles

Aperçu

Get prepared for the AI-900 exam with instructor led labs and hands on simulations available 24/7 What you'll learn:

Learn the concepts and perform hands on activities needed to pass the AI-900 examGain a tremendous amount of knowledge involving advanced Azure AI ServicesGet loads of hands on experience with Azure AI ServicesUtilize hands on simulations that can be access anytime, anywhere! We really hope you'll agree, this training is way more than the average course on Udemy!

Have access to the following:

Training from an instructor of over 25 years who has trained thousands of people and also a Microsoft Certified TrainerLecture that explains the concepts in an easy to learn method for someone that is just starting out with this materialInstructor led hands on and simulations to practice that can be followed even if you have little to no experienceTOPICS COVEREDINCLUDINGHANDSONLECTUREANDPRACTICETUTORIALS:

IntroductionWelcome to the courseIMPORTANT Using Assignments in the courseCreating a free Azure AccountOrder of concepts covered in the courseIntroduction to artificial intelligence terminologyIdentify features of common AI workloadsUnderstanding features of anomaly detection workloadsExample of univariate anomaly detectionExample of multivariate anomaly detectionWhat is computer vision workloads?Conceptual usage of natural language processing workloadsVisualizing knowledge mining principalsIdentify guiding principles for responsible AIIntroduction to responsible AIFairness and Inclusiveness in an AI solutionReliability and safety in an AI solutionPrivacy and security in an AI solutionTransparency in an AI solutionAccountability in an AI solutionIdentify common machine learning typesCreate an Azure Machine Learning workspace for machine learning scenariosWhat is regression machine learning?Building a pipeline with regression machine learning for cleaning a datasetImplement a regression machine learning scenarioEvaluating the results of regression machine learning scenariosWhat is classification machine learning?Implement a classification machine learning scenario in AzureUnderstanding labels on a confusion matrixClustering machine learning exampleDescribe core machine learning conceptsUnderstanding features and labels in a dataset for machine learningHow training and validation datasets are used in machine learningDescribe capabilities of visual tools in Azure Machine Learning StudioUsing Automated machine learningUnderstanding Azure Machine Learning DesignerCleaning up our existing Azure resourcesIdentify common types of computer vision solutionsWhat are the Azure computer vision solutions?Creating an Azure computer vision resourceImage classification and object detection solutions in vision studioOptical character recognition solutions in vision studioFacial detection and facial analysis solutions in vision studioSpatial analysis solutions in vision studioIdentify Azure tools and services for computer vision tasksUsing the POSTMAN tool for interacting with Azure AI ServicesImplementing the capabilities of the Computer Vision serviceImplementing the capabilities of the Custom Vision serviceImplementing the capabilities of the Face serviceImplementing the capabilities of the Form Recognizer serviceIdentify features of common NLP Workload ScenariosWhat are the Azure AI Language features?Creating a language service resource in AzureTrying out key phrase extractionTrying out key entity recognitionTrying out key sentiment analysisTrying out key language modelingTrying out key speech recognition and synthesisTrying out key translationIdentify Azure tools and services for NLP workloadsExploring the capabilities of the Language serviceExploring the capabilities of the Speech serviceExploring the capabilities of the Translator serviceConfiguring Azure AI language to support questions and answers supportIdentify considerations for conversational AI solutions on AzureUnderstanding the features and uses for botsCapabilities of Power Virtual Agents and the Azure Bot serviceRemove existing resourceIdentify features and capabilities of generative AI & the Azure Open AI ServiceFeatures of generative Open AI modelsCommon scenarios for generative Open AIResponsible Open AI considerations for generative AI

Programme

• Introduction à l'IA et fondamentaux de l'IA Azure
Aperçu des concepts et définitions de l'IA
Introduction aux services Microsoft Azure AI
• Premiers pas avec Azure
Création d'un compte Azure
Navigation dans le portail Azure
Compréhension des offres de services Azure AI
• Concepts de l'apprentissage automatique
Introduction à l'apprentissage automatique (ML) et à ses applications
Apprentissage supervisé vs apprentissage non supervisé
Aperçu de Microsoft Azure Machine Learning Studio
• Traitement du langage naturel (NLP)
Comprendre le NLP et ses cas d'utilisation
Introduction aux services cognitifs Azure pour la langue
Analyse de texte et analyse de sentiment
• Vision par ordinateur
Notions de base sur la vision par ordinateur
Services cognitifs Azure pour la vision
Traitement et analyse d'images avec Azure
• IA conversationnelle et bots
Introduction à l'IA conversationnelle
Création de chatbots avec Azure Bot Service
Intégration de l'IA dans les chatbots avec Language Understanding (LUIS)
• IA responsable et éthique
Principes de l'IA responsable
Considérations éthiques dans le développement et le déploiement de l'IA
Outils et meilleures pratiques pour l'équité et la transparence de l'IA
• Simulations virtuelles Azure AI
Laboratoires et simulations virtuels pratiques
Scénarios d'IA réels et études de cas
Utilisation des outils Azure AI dans des environnements simulés
• Préparation à l'examen
Compréhension du format de certification AI-900
Révision des concepts clés et des offres de services
Questions de pratique et stratégies d'examen
• Évaluation finale et fin de formation
Réalisation de l'évaluation finale du cours
Retour d'expérience et revue du cours
Certification de fin et prochaines étapes

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Enseigné par

John Christopher

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Matières

Programming