AI-900: Microsoft Azure AI Fundamentals Course - May 2022

Should you take AI-900 Exam?Artificial intelligence and machine learning are all set to dictate the future of technology. The focus of Microsoft Azure on machine-learning innovation is one of the prominent reasons for the rising popularity of Azure AI. Therefore, many aspiring candidates are looking for credible approaches for the AI-900 exam preparation that is a viable instrument for candidates to start their careers in Azure AI. The interesting fact about the AI-900 certification is that it is a fundamental-level certification exam. Therefore, candidates from technical as well as ones with non-technical backgrounds can pursue the AI-900 certification exam. In addition, there is no requirement for software engineering or data science experience for the AI-900 certification exam. The AI-900 certification can also help you build the foundation for Azure AI Engineer Associate or Azure Data Scientist Associate certifications. Course last updated - May 2022~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~What includes in this course?8+ hrs. of content, Practice test, quizzes, etc. PPT, Demo resources, and other study materialFull lifetime accessCertificate of course completion30-days Money-Back GuaranteeThis course has more than enough practice questions to get you to prepare for the exam. Even though there are no labs in the exam, I have practically demonstrated concepts wherever possible to make sure you feel confident with concepts. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Exam Format and InformationExam Name Exam AI-900: Microsoft Azure AI FundamentalsExam Duration 60 MinutesExam Type Multiple Choice ExaminationNumber of Questions 40 - 60 QuestionsExam Fee $99Eligibility/Pre-requisite NoneExam validity 1 yearExam Languages English, Japanese, Korean, and Simplified Chinese~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~The AI-900 exam covers the following topics: Describe AI workloads and considerations (15-20%)Describe fundamental principles of machine learning on Azure (30-35%)Describe features of computer vision workloads on Azure (15-20%)Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)Describe features of conversational AI workloads on Azure (15-20%)~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Exam Topics in detailDomain 1: Describing AI workloads and considerationsThe subtopics in this domain include, Identification of features in common AI workloadsIdentification of guiding principles for responsible AIDomain 2: Describing fundamental principles of machine learning on AzureThe subtopics in this domain include, Identification of common machine learning variantsDescription of core machine learning conceptsIdentification of core risks in the creation of a machine learning solutionDescription of capabilities of no-code machine learning with Azure Machine LearningDomain 3: Description of features in computer vision workloads on AzureThe subtopics in this domain include, Identification of common types of computer vision solutionsIdentification of Azure tools and services for computer vision tasksDomain 4: Describing features of Natural Language Processing (NLP) workloads on AzureThe subtopics in this domain are as follows, Identification of features in common NLP workload scenariosIdentifying Azure tools and services for NLP workloadsDomain 5: Description of features of conversational AI workloads on AzureThe subtopics in this domain include, Identification of common use cases for conversational AIIdentifying Azure services for conversational AIHappy Learning!! Eshant Garg