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Describe NLP Workloads Features on Azure (15-20%)
This domain contains the following details that you need to learn about:
- Identify the features of basic NLP (Natural Language Processing) Workload Scenarios – The individuals should be able to identify various uses and features of various components, for example, keyphrase extraction, sentiment analysis, entity recognition, translation, language modeling, and speech recognition & synthesis.
- Identify Azure services & tools for Natural Language Processing Workloads – This topic is created to equip you with the ability to identify various capabilities, such as Speech service, Text Analytics service, Translator Text service, and Language Understanding service.
What is Microsoft AI-900 Exam
Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. Explore the objectives of the AI-900 exam. Protection of the Azure platform and its components. Reference architecture for Azure solutions. Implementation, configuration, and management of Azure services. Request, manage and monitor Azure services. Troubleshooting of Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam takers level of competence in the functions, features, and services of Azure. Depth and Breadth of Knowledge. Processes and practices for developing and deploying intelligent solutions. Hope you like this article. Associate in IT, Eugene is an expert in the fields of software applications and internet technologies. Paying attention to the latest technology is the reason Eugene uses his knowledge of high-end computer systems, application programming, and data entry.
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
What is the duration, language, and format of AI-900: Microsoft Azure AI Fundamentals Exam
- Length of Examination: 50 mins
- Number of Questions: 100 to 120 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice)
- Type of Questions: This test format is multiple choice
- Languages in which this exam is available in: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish
- Passing Score: 70%
Microsoft AI-900 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Certificate Validity Period: | No expiration (certification does not expire) |
| Available Languages: | English, Spanish, Chinese (Simplified), Portuguese (Brazil), French, German, Indonesian, Korean, Japanese |
| Passing Score: | 700/1000 |
| Exam Duration: | 45-60 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Format: | Multiple-choice, True/False, Drag and drop, Single-choice, Sequence ordering |
| Real Exam Qty: | 40-60 |
| Exam Price: | USD 99.00 |
| Sample Questions: | Microsoft AI-900 Sample Questions |
| Exam Way: | Online proctored exam or in-person testing center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required. Basic knowledge of cloud computing concepts is recommended but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/ai-900/ |
Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe features of Generative AI workloads on Azure | 15-20% | - Describe Azure OpenAI Service capabilities - Identify responsible AI considerations for generative AI - Describe generative AI concepts |
| Topic 2: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Identify Azure AI services for NLP - Describe Azure capabilities for NLP |
| Topic 3: Describe fundamental principles of machine learning on Azure | 30-35% | - Describe Azure Machine Learning capabilities - Identify common machine learning tasks - Describe core machine learning concepts - Describe features of no-code automated ML |
| Topic 4: Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Topic 5: Describe features of computer vision workloads on Azure | 15-20% | - Identify common computer vision tasks - Identify Azure AI services for computer vision - Describe Azure capabilities for computer vision |
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