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uCertifyPrep Azure Fundamental im Vergleich zu Azure AI Fundamentals Quiz Nutzung und Statistiken
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 Fundamentalvs. Azure AI Fundamentals Quiz Ranking-Vergleich
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uCertifyPrep Azure Fundamental VS.
Azure AI Fundamentals Quiz
Dezember 11, 2024