AI-900 Exam: Microsoft Azure AI Fundamentals || 8+ hours of videos || 100% Syllabus || 2 Practice Tests || PPTs || Demos
Should you take AI-900 Exam?
What you’ll learn
- Foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services..
- Common ML and AI workloads and how to implement them on Azure..
- AI workloads and considerations: AI-900 Exam.
- Principles of machine learning on Azure: AI-900 Exam.
- Computer vision workloads on Azure: AI-900 Exam.
- Natural Language Processing (NLP) workloads on Azure: AI-900 Exam.
- Conversational AI workloads on Azure: AI-900 Exam.
Course Content
- Introduction –> 4 lectures • 10min.
- Azure Portal Introduction: For Begineers –> 4 lectures • 27min.
- AI workloads and considerations (15-20%) –> 17 lectures • 1hr 19min.
- Fundamental principles of Machine Learning on Azure (30- 35%) –> 15 lectures • 3hr 1min.
- Describe features of computer vision workloads on Azure (15-20%) –> 15 lectures • 1hr 49min.
- Natural Language Processing (NLP) workloads on Azure (15-20%) –> 13 lectures • 1hr 24min.
- Conversational AI workloads on Azure (15-20%) –> 6 lectures • 46min.
- Practice Tests –> 4 lectures • 8min.
- Wrapping up –> 1 lecture • 1min.
Requirements
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.
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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 completion
- 30-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.
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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 $99
Eligibility/Pre-requisite None
Exam validity 1 year
Exam Languages English, Japanese, Korean, and Simplified Chinese
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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%)
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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 AI
Domain 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 AI
- Identifying Azure services for conversational AI
Happy Learning!!
Eshant Garg