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Microsoft Azure AI Fundamentals Exam Certification Details:
Exam Name | Microsoft Certified - Azure AI Fundamentals |
Schedule Exam | Pearson VUE |
Books / Training | Course AI-900T00: Microsoft Azure AI Fundamentals |
Sample Questions | Microsoft Azure AI Fundamentals Sample Questions |
Exam Price | $99 (USD) |
Number of Questions | 40-60 |
Exam Code | AI-900 |
Duration | 60 mins |
Passing Score | 700 / 1000 |
Microsoft AI-900 Exam Syllabus Topics:
Topic | Details |
---|---|
Describe Artificial Intelligence workloads and considerations (20-25%) | |
Identify features of common AI workloads | - identify features of anomaly detection workloads - identify computer vision workloads - identify natural language processing workloads - identify knowledge mining workloads |
Identify guiding principles for responsible AI | - describe considerations for fairness in an AI solution - describe considerations for reliability and safety in an AI solution - describe considerations for privacy and security in an AI solution - describe considerations for inclusiveness in an AI solution - describe considerations for transparency in an AI solution - describe considerations for accountability in an AI solution |
Describe fundamental principles of machine learning on Azure (25-30%) | |
Identify common machine learning types | - identify regression machine learning scenarios - identify classification machine learning scenarios - identify clustering machine learning scenarios |
Describe core machine learning concepts | - identify features and labels in a dataset for machine learning - describe how training and validation datasets are used in machine learning |
Describe capabilities of visual tools in Azure Machine Learning studio | - automated machine learning - azure Machine Learning designer |
Describe features of computer vision workloads on Azure (15-20%) | |
Identify common types of computer vision solution | - identify features of image classification solutions - identify features of object detection solutions - identify features of optical character recognition solutions - identify features of facial detection, facial recognition, and facial analysis solutions |
Identify Azure tools and services for computer vision tasks | - identify capabilities of the Computer Vision service - identify capabilities of the Custom Vision service - identify capabilities of the Face service - identify capabilities of the Form Recognizer service |
Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%) | |
Identify features of common NLP Workload Scenarios | - identify features and uses for key phrase extraction - identify features and uses for entity recognition - identify features and uses for sentiment analysis - identify features and uses for language modeling - identify features and uses for speech recognition and synthesis - identify features and uses for translation |
Identify Azure tools and services for NLP workloads | - identify capabilities of the Language service - identify capabilities of the Speech service - identify capabilities of the Translator service |
Identify considerations for conversational AI solutions on Azure | - identify features and uses for bots - identify capabilities of the Azure Bot service |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Explain Conversational Artificial Intelligence Workloads Features on Azure (15-20%)
In the last section, you will face with the following subtopics:
- Identify the basic use cases for Conversational Artificial Intelligence (AI) – The students should be able to identify the features and usage for a range of elements. These include personal digital assistants, webchat bots, and telephone voice menus. It also covers the skills in identifying the basic features of conversational Artificial Intelligence solutions.
- Establish Azure services for Conversational Artificial Intelligence – The potential candidates for the Microsoft AI-900 exam should have the capacity to identify the capabilities of Azure Bot Service and QnA Maker service.
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