uCertifyPrep Azure Fundamental vs. Azure AI Fundamentals Quiz Utilizzo e statistiche

uCertify Azure Fundamental TestPrep is a full-length practice test that can be configured to closely follow the exam objectives and is designed to simulate real testing conditions. The TestPrep prepares one for high-level concepts that are specific to a particular Azure service and teaches about cloud concepts, Azure services, Azure workloads, security and privacy in Azure, as well as Azure pricing and support. It allows you to study anywhere, anytime, right from your mobile device. It is a simple, cloud-based solution that can be used effortlessly to prepare for CompTIA Azure Fundamental certification. We attempt to make your learning more efficient by redefining your preparation. uCertify Azure Fundamental TestPrep Features: -Uses any of the 50+ item types including auto-graded performance items -For formative tests, students receive feedback and reinforcement, therefore, improving their test-taking skills and strategies -Available both as a standalone product and also as part of the uCertify course -Offers uCertify Play - a gamified version of TestPrep that has a deep foundation in learning science. -uCertify Play helps students both retain and recall better by using randomization, mastery, and spaced learning. uCertify TestPrep questions are designed by subject matter experts who ensure that learners prepare under actual exam conditions using the item-types expected to appear in the actual certification exam. Need help regarding our features? Please contact https://www.ucertify.com/support.php with your queries or suggestions. We are available 24x7!
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Skills Measured: Describe Artificial Intelligence workloads and considerations (15-20%) Identify features of common AI workloads Identify prediction/forecasting workloads Identify features of anomaly detection workloads Identify computer vision workloads Identify natural language processing or knowledge mining workloads Identify conversational AI workloads Identify guiding principles for responsible AI Describe considerations for fairness in an AI solution Describe considerations for reliability and safety in an AI solution Describe considerations for privacy and security in an AI solution Describe considerations for inclusiveness in an AI solution Describe considerations for transparency in an AI solution Describe considerations for accountability in an AI solution Describe fundamental principles of machine learning on Azure (30- 35%) Identify common machine learning types Identify regression machine learning scenarios Identify classification machine learning scenarios Identify clustering machine learning scenarios Describe core machine learning concepts Identify features and labels in a dataset for machine learning Describe how training and validation datasets are used in machine learning Describe how machine learning algorithms are used for model training Select and interpret model evaluation metrics for classification and regression Identify core tasks in creating a machine learning solution Describe common features of data ingestion and preparation Describe feature engineering and selection Describe common features of model training and evaluation Describe common features of model deployment and management Describe capabilities of no-code machine learning with Azure Machine Learning studio Automated ML UI Azure Machine Learning designer Describe features of computer vision workloads on Azure (15-20%) Identify common types of computer vision solution: Identify features of image classification solutions Identify features of object detection solutions Identify features of optical character recognition solutions Identify features of facial detection, facial recognition, and facial analysis solutions Identify Azure tools and services for computer vision tasks Identify capabilities of the Computer Vision service Identify capabilities of the Custom Vision service Identify capabilities of the Face service Identify capabilities of the Form Recognizer service Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) Identify features of common NLP Workload Scenarios Identify features and uses for key phrase extraction Identify features and uses for entity recognition Identify features and uses for sentiment analysis Identify features and uses for language modeling Identify features and uses for speech recognition and synthesis Identify features and uses for translation Identify Azure tools and services for NLP workloads Identify capabilities of the Text Analytics service Identify capabilities of the Language Understanding service (LUIS) Identify capabilities of the Speech service Identify capabilities of the Translator Text service Describe features of conversational AI workloads on Azure (15-20%) Identify common use cases for conversational AI Identify features and uses for webchat bots Identify common characteristics of conversational AI solutions Identify Azure services for conversational AI Identify capabilities of the QnA Maker service Identify capabilities of the Azure Bot service
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uCertifyPrep Azure Fundamental VS.
Azure AI Fundamentals Quiz

12icembre d, 2024