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

 Buy Now
  

Price: 24.99$

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 material Full lifetime access Certificate of course completion30-days Money-Back Guarantee This 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 Information Exam Name Exam AI-900: Microsoft Azure AI Fundamentals Exam Duration 60 Minutes Exam Type Multiple Choice Examination Number of Questions 40 – 60 Questions Exam Fee $99Eligibility/Pre-requisite None Exam validity 1 year Exam 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 detail Domain 1: Describing AI workloads and considerations The subtopics in this domain include, Identification of features in common AI workloads Identification of guiding principles for responsible AIDomain 2: Describing fundamental principles of machine learning on Azure The subtopics in this domain include, Identification of common machine learning variants Description of core machine learning concepts Identification of core risks in the creation of a machine learning solution Description of capabilities of no-code machine learning with Azure Machine Learning Domain 3: Description of features in computer vision workloads on Azure The subtopics in this domain include, Identification of common types of computer vision solutions Identification of Azure tools and services for computer vision tasks Domain 4: Describing features of Natural Language Processing (NLP) workloads on Azure The subtopics in this domain are as follows, Identification of features in common NLP workload scenarios Identifying Azure tools and services for NLP workloads Domain 5: Description of features of conversational AI workloads on Azure The subtopics in this domain include, Identification of common use cases for conversational AIIdentifying Azure services for conversational AIHappy Learning!! Eshant Garg