AI-900: Microsoft Azure AI Fundamentals Exam Study Guide

Artificial Intelligence (AI) is taking over the IT world and the improvement of AI is evident. Thus, AI 900 certification is a great choice for future cloud professionals to acquire the fundamental understanding of the field of machine learning as well as AI concepts.

AI-900 Microsoft Azure AI Fundamentals is a widely acknowledged certification that proves the candidate’s understanding of Artificial Intelligence (AI) and Machine Learning (ML) concepts and their corresponding Microsoft Azure services. The Azure AI Fundamentals exam requires candidates to demonstrate commonly used AI and ML tasks and their application in Azure.

The topics covered in this blog are:

• What is Azure AI Fundamentals Certification?
• Why use Azure AI Solutions?
• Who Can Do This Certification?
• Benefits of AI-900 Certification
• AI-900 Exam Details
• AI-900 Exam Skills Measured
• How to Register for Azure AI 900 Exam
• Pre-requisites for AI-900 Certification
• Azure AI Fundamentals Certification (AI 900) Study Guide
• AI 900 Exam Day Tips
• Conclusion
• FAQs

What Is Azure AI Fundamentals Certification?

AI 900 certificate is an essential grade accreditation for information researchers to have a thought of how to apply AI and Machine Learning in their calling. Additionally, it likewise affirms you for utilizing Azure administrations connected with ML and AI. What’s more, we can utilize the AI900 Microsoft Azure AI Fundamentals accreditation test as a significant device for exhibiting an intensive comprehension of general ML and AI responsibilities.

Are you a beginner in the Azure cloud? Do check out our blog post on the Azure Certification Path and choose the best certification for you.

Why Use Azure AI solutions?

The justification for why one should change to Azure AI arrangement can be shown through different reasons:

• It gives a cloud stage for executing AI Solutions
• It gives no-code ML models to handling information.
• It helps in executing and checking AI arrangements.
• You can plan AI as financially savvy Intelligent Edge arrangements.
• You can plan and distinguish information administration, and necessities.

Who Can Do This Certification?

This test can be endeavored by the competitors getting ready for the Azure AI Fundamentals AI-900 confirmation test.

This test is reasonable for individuals with both specialized and non-specialized foundations who need to show a sense of man-made brainpower and AI.

Benefits of AI-900 Certification

The advantages of going to this test are as per the following:

1. Because of the soaring development of AI, the significance of Azure AI Engineers is likewise apparent.
2. The volume of deciphering the vision of cloud engineer for the advancement of start to finish arrangements utilizing AI and ML on Azure.
3. It will further develop your acquiring potential.
4. Azure AI engineers need to work as a team with information engineers, information researchers, AI designers, and IoT experts as these jobs are related.

Also Check: Azure Data Factory Interview Questions

AI-900 Exam Details

AI-900 Exam Skills Measured

How to Register for Azure AI 900 Exam

You can register for Microsoft Azure Data Fundamentals Exam (AI900) by going to the official Microsoft page.

Pre-requisites for AI-900 Certification

There are no pre-requisites for the AI-900 exam.

Also Read: What is Azure?

Azure AI Fundamentals Certification (AI 900) Study Guide

Describe Artificial Intelligence Workloads and Considerations (15-20%)

Identify Features of Common AI Workloads

• identify prediction/forecasting workloads
  • Demand forecasting
  • Demand forecasting & price optimization
  • Demand forecasting for shipping and distribution
  • Personalized offers
• identify features of anomaly detection workloads
  • Anomaly Detector
• identify computer vision workloads
  • Detect common objects in images
  • Detect popular brands in images
  • Apply content tags to images
  • Categorize images by subject matter
  • Describe images with human-readable language
• identify natural language processing or knowledge mining workloads
  • Natural language processing technology
• identify conversational AI workloads
  • Microsoft Conversational AI tools: To build, connect and manage intelligent bots

 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
  • Microsoft Responsible AI principles

Describe fundamental principles of machine learning on Azure (30- 35%)

Identify common machine learning types

• identify regression machine learning scenarios
  • Linear Regression
• identify classification machine learning scenarios
  • Classification modules
• identify clustering machine learning scenarios
  • Clustering modules

Describe core machine learning concepts

• identify features and labels in a dataset for machine learning
  • Framing: Key ML Terminology
• describe how training and validation datasets are used in machine learning
  • How to Train, Validation and Test Sets in Machine Learning
• describe how machine learning algorithms are used for model training
  • Which machine learning algorithm should I use?
• select and interpret model evaluation metrics for classification and regression
  • Metrics for classification models
  • Metrics for regression models

Identify core tasks in creating a machine learning solution

• describe common features of data ingestion and preparation
  • Data ingestion
  • What is Data Preparation for Machine Learning?
• describe feature engineering and selection
  • Python Feature Selection Tutorial
  • Feature Engineering
• describe common features of model training and evaluation
  • ML Model Training
  • Evaluate Model
  • Machine Learning Model Evaluation
• describe common features of model deployment and management
  • Deploy real-time ML services with Azure ML
  • MLOps

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

• Automated ML UI
  • What is automated machine learning (AutoML)?
• Azure Machine Learning designer
  • What is an 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
  • Train and deploy an image classification model
• identify features of object detection solutions
  • Detect common objects in images
• identify features of optical character recognition solutions
  • What is Optical character recognition?
• identify features of facial detection, facial recognition, and facial analysis solutions
  • Face detection and attributes
  • Face recognition concepts
  • How to Analyze Videos in Real-time

Identify Azure tools and services for computer vision tasks

• identify capabilities of the Computer Vision service
  • What is Computer Vision?
• identify capabilities of the Custom Vision service
  • What is Custom Vision?
• identify capabilities of the Face service
  • What is the Azure Face service?
• identify capabilities of the Form Recognizer service
  • What is Azure Form Recognizer?

Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)

Identify features of common NLP Workload Scenarios

• identify features and uses for keyphrase extraction
  • What is key phrase extraction in Azure Cognitive Service for Language?
• identify features and uses for entity recognition
  • Entity Recognition cognitive skill
• identify features and uses for sentiment analysis
  • Sentiment Analysis with Cognitive Service and Azure
• identify features and uses for language modeling
  • MSRLM: Language Modeling Toolkit
• identify features and uses for speech recognition and synthesis
  • What is the Speech service?
  • Recognize and convert speech to text
• identify features and uses for translation
  • Translator App Features

Identify Azure tools and services for NLP workloads

• identify capabilities of the Text Analytics service
  • What is Azure Cognitive Service for Language?
• identify capabilities of the Language Understanding service (LUIS)
  • What is Language Understanding (LUIS)?
• identify capabilities of the Speech service
  • What is the Speech service?
• identify capabilities of the Translator Text service
  • Text Translation

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

Identify common use cases for conversational AI

• identify features and uses for webchat bots
  • Web Chat overview
• identify common characteristics of conversational AI solutions
  • Microsoft Conversational AI tools

 Identify Azure services for conversational AI

• identify capabilities of the QnA Maker service
  • What is QnA Maker?
• identify capabilities of the Azure Bot Service
  • Azure Bot Service

AI-900 Exam Day Tips

Before attempting the exam, the candidate must keep in mind these tips if they wish to qualify for the exam:

• Run a System Check before the test.
• There can be a variety in the test question types like fill in the spaces, valid or bogus, various responses, numerous decisions, simplified, fill the missing modules in the given pipeline, so be ready for it!
• Be cautious and speed yourself on the inquiries so as not to stall out on one query for extremely lengthy.
• Simply skip the new queries and return to them later.
• Breaks will be not be permitted during the test.

Conclusion

In this Azure tutorial, we discussed What is Azure AI Fundamentals Certification, Who Can Do This Certification, benefits, Exam Details, Study Guide, and much more.

I hope you have enjoyed this article!!!

FAQs

Related/References

• Microsoft Azure Certification Study Guides
• AI-900 Study Guide PDF
• AZ-900 Study Guide
• Azure Durable Functions
• What is Microsoft Azure Recovery Services Vault?
• Introduction to Microsoft Azure Blueprints
• Azure Application Gateway
• What is Azure ExpressRoute?
• What is Azure Data Lake?