Microsoft Azure AI Fundamentals AZ-900 Certification Overview

April 18, 2022April 18, 2022 LisaLisa 0 Comments

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Microsoft Certified: Azure AI Fundamentals

Candidates for the Azure AI Fundamentals certification should have a foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

This certification is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This certification is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.

Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.

Job Role:

AI Engineer
Developer
Data Scientist
Student

Required Exams: AI-900

Certification Details

Take one exam: AI-900: Microsoft Azure AI Fundamentals

Earn the certification: Microsoft Certified: Azure AI Fundamentals

Exam AI-900: Microsoft Azure AI Fundamentals

Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish

Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

Exam AI-900: Microsoft Azure AI Fundamentals

Candidates for this exam should have a foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial.

Part Of The Requirements For: Microsoft Certified: Azure AI Fundamentals

Related Exams: none

Skills Measured:

Describe Artificial Intelligence workloads and considerations (15-20%)

Identify features of common AI workloads

identify prediction/forecasting workloads
identify features of anomaly detection workloads
identify computer vision workloads
identify natural language processing or knowledge mining workloads
identify conversational AI 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 (30-35%)

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 how machine learning algorithms are used for model training
select and interpret model evaluation metrics for classification and regression

Identify core tasks in creating a machine learning solution

describe common features of data ingestion and preparation
describe feature engineering and selection
describe common features of model training and evaluation
describe common features of model deployment and management

Describe capabilities of no-code machine learning with Azure Machine Learning studio

automated ML UI
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 semantic segmentation 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 (15-20%)

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 Text Analytics service
identify capabilities of the Language Understanding service (LUIS)
identify capabilities of the Speech service
identify capabilities of the Translator Text service

Describe features of conversational AI workloads on Azure (15-20%)

Identify common use cases for conversational AI

identify features and uses for webchat bots
identify features and uses for telephone voice menus
identify features and uses for personal digital assistants
identify common characteristics of conversational AI solutions

Identify Azure services for conversational AI

identify capabilities of the QnA Maker service
identify capabilities of the Azure Bot service

Preparing For The Exam

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Conclusion

Cloud computing is one of the fastest-growing technologies of the present era. With more organizations migrating to the cloud platform from conventional on-premises infrastructure, it has seen phenomenal growth in the job market as well. A large number of professionals with cloud platform-related skills are required by the market. Microsoft is among the second-largest cloud platform in the world. Microsoft Azure is the most popular cloud platform in the enterprise market. Microsoft Azure platform certifications are valuable credentials for the job market. Microsoft Certified: Azure AI Fundamentals is a single exam valued certification for beginners that can be earned with a single Exam AI-900: Microsoft Azure AI Fundamentals.