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How to Register For Exam AI-900: Microsoft Azure AI Fundamentals?
Learning Path
All in all, Microsoft provides two ways to help candidates prepare for the Microsoft AI-900 exam. These include the free online learning option and the paid, instructor-led training. Let’s discuss the two most popular courses offered by each of these options by the vendor:
- Microsoft Azure AI Fundamentals
This one-day course is part of the instructor-led learning platform and is, therefore, a paid option. As the name suggests, it is meant to introduce the candidates to fundamental AI concepts. The training, in particular, emphasizes the skills you need to become well versed in AI workloads and understand the Azure services that support such solutions. Usually, the course curriculum is viewed as comprehensive blended learning, featuring a combination of online materials and instructor-led training to ensure candidates have a good grasp of the exam topic areas. Even more, the hands-on exercises that are featured here are meant to help learners understand the test domains in real-world scenarios. Familiarity with the internet and computer technology is not a prerequisite but a great combination that will go a long way toward helping you register excellent results in this course and the ultimate exam.
- Get Started with Artificial Intelligence
The online gratis class, “Get Started with Artificial Intelligence” features one module and is intended to run for a maximum of 34 minutes. In general, this course is designed to help you get started with Microsoft services that empower new AI solutions. There are no prerequisites associated with this training. However, it features one module with a total of 10 units including the introduction and an understanding of machine learning, anomaly detection, computer vision, natural language processing, conversational AI, and responsible AI just to mention a few. Visit the official certification page to find out more information about this learning path that also includes classes on ML, NLP, and conversational AI.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
The Microsoft certificate stands out among the numerous certificates because its practicability and role to improve the clients' stocks of knowledge and practical ability. Owning a test Microsoft certificate equals owning a weighty calling card when the clients find jobs and the proof that the clients are the competent people. Our AI-900 Korean quiz prep is the great option for the clients to prepare for the test. Our AI-900 Korean study materials boost high passing rate and hit rate. Our clients praise them highly after they use them and recognize them as the key tool to pass the Microsoft certification. We are never satisfied with the present situation and expand and update the AI-900 Korean exam practice guide by all means. We focus on the innovation and organize our expert team to compile new knowledge points and update the test bank. We treat our clients as our god and treat their supports to our AI-900 Korean study materials as our driving forces to march forward.
How to book the AI-900: Microsoft Azure AI Fundamentals Exam
- Step 1: Visit to Microsoft Learning and search for AI-900: Microsoft Azure AI Fundamentals Exam Outlook and Modules.
- Step 2: Sign up/Login to Pearson VUE account.
- Step 3: Select local centre based on your country, date, time and confirm with a payment method.
Microsoft AI-900 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Identify types of NLP solutions - Describe capabilities of Azure Translator - Describe capabilities of Azure Language |
| Topic 2: Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Topic 3: Fundamental principles of machine learning on Azure | 15–20% | - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning - Describe automated machine learning - Describe core concepts of machine learning |
| Topic 4: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Face - Describe capabilities of Azure Custom Vision - Identify types of computer vision solutions - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer |
| Topic 5: Features of generative AI workloads on Azure | 20–25% | - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts - Describe use cases for generative AI |







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