Training Overview
This training introduces fundamental concepts related to artificial intelligence (AI) & the services in Microsoft Azure that can be used to create AI solutions. The training is not designed to teach professionals to become professional data scientists/ software developers but rather to build awareness of typical AI workloads & the capability to identify Azure services to support them. The training is a learning experience combining instructor-led tutoring with online materials on the Microsoft learning platform (https://azure.com/learn). The hands-on exercises in this training are based on Learn modules, & professionals are encouraged to use the content on understanding as reference materials to reinforce what they understand in the class & to explore topics in more depth.
Duration: 1 Day
Learning Objectives:
Pre-requisites
Pre-requisite certification is optional before taking this training. Successful Azure AI Fundamental professionals start with some essential awareness of computing & internet concepts & an interest in using Azure AI services.
Specifically:
Experience using computers & the Internet.
Interest in use cases for AI applications & machine learning models.
A willingness to learn through hands-on exploration
Audience Profile
The Azure AI Fundamentals training is designed for anyone interested in understanding the types of solutions artificial intelligence (AI) makes possible & the services on Microsoft Azure that you may use to create them. You don't need to have any experience using Microsoft Azure before taking this training, but a basic familiarity with computer technology & the Internet is assumed. Some of the concepts covered in training require basic mathematics understanding, such as the ability to interpret charts. The training includes hands-on activities that involve working with data & running code, so a knowledge of fundamental programming principles will be helpful.
Content Outline
Get started with AI on Azure.
In this module, you'll learn about the various kinds of solutions AI can make possible & considerations for responsible AI practices.
Using AI, we can create solutions that seemed like science fiction a short time ago, allowing incredible advances in health care, environmental protection, financial management, & other areas to make a better world for everyone.
Using automated machine learning in azure machine learning
Machine learning model training is an iterative process that requires time & computing resources. Automated machine learning can make it simpler.
Understand how to use the automated machine learning user interface in Azure Machine Learning
Creating a regression model with Azure Machine Learning designer
Regression is a supervised machine-learning technique used to predict numeric values. Understand how to create regression models using Azure Machine Learning designer.
Learn how to train & publish a regression model with Azure Machine Learning designer
Creating a classification model with Azure Machine Learning designer
Classification is a supervised machine learning technique that requires classes or predicted categories. Understand how to create classification models using Azure Machine Learning designer.
Train & publish a classification model with Azure Machine Learning designer.
Creating a clustering model with Azure Machine Learning designer
Clustering is an unsupervised machine-learning technique used to group similar entities based on their features. Understand how to create clustering models using Azure Machine Learning designer.
Train & publish a clustering model with Azure Machine Learning designer.
Analyzing images with the Computer Vision service
The Computer Vision service allows software engineers to create intelligent solutions extracting information from images, a common task in many artificial intelligence (AI) scenarios.
Learning how to use the Computer Vision cognitive service to analyze images
Classifying images with the Custom Vision service
Image classification is a common workload in AI (artificial intelligence) applications. This harnesses the predictive power of machine learning, allowing AI systems to identify real-world items based on images.
Learning how to use the Custom Vision service to create an image classification solution.
Detecting objects in images with the custom vision service
Object detection is a form of computer vision in which AI (artificial intelligence) agents can identify & locate specific types of objects in an image or camera feed.
Learning how to use the Custom Vision service to create an object detection solution.
Detect & analyze faces with the Face service
Face detection, analysis, & recognition are essential capabilities for AI (artificial intelligence) solutions. The face cognitive service in Azure makes it simple to integrate these capabilities into your applications.
Learning how to use the Face cognitive service to detect & analyze faces in images.
Read the text with the Computer Vision service.
Optical character recognition (OCR) allows artificial intelligence (AI) systems to read the text in images, allowing the applications to extract information from photographs, scanned documents, & other sources of digitized text.
Learn how to read the text in images with the Computer Vision service
Analyze receipts with the Form Recognizer service
Processing invoices & receipts is a common task in many business scenarios. Organizations are turning to AI (artificial intelligence) to automate data extraction from scanned receipts.
Understand using the built-in receipt processing capabilities of the Form Recognizer service
Analyze text with the Language service
Explore text mining & text analysis with the Language service's Natural Language Processing (NLP) features, including sentiment analysis, key phrase extraction, named entity recognition & language detection.
Learning how to use the Language service for text analysis
Recognize & synthesize speech
In this module, you will:
- Learn about speech recognition & synthesis
- Learning how to use the Speech cognitive service in Azure
Translate text & speech:
Automated translation capabilities in an AI solution allow closer collaboration by removing language barriers.
After completing this module, you can perform text & speech translation using Azure Cognitive Services.
Creating a language model with Conversational Language Understanding
In this module, you'll:
- Learn what Conversational Language Understanding is.
- Learn about key features, such as intents & utterances.
- Build & publish a natural-language machine-learning model.
Building a bot with the language Service & azure bot service
Bots are a popular way to provide support through multiple communication channels. The module describes how to use a knowledge base & Azure Bot Service to create a bot that answers user questions.
After finishing this module, you will be able to build a knowledge base with an Azure Bot Service bot.
Get started with AI on Azure.
In this module, you'll learn about the various kinds of solutions AI can make possible & considerations for responsible AI practices.
Using AI, we can create solutions that seemed like science fiction a short time ago, allowing incredible advances in health care, environmental protection, financial management, & other areas to make a better world for everyone.
Machine learning model training is an iterative process that requires time & computing resources. Automated machine learning can make it simpler.
Understand how to use the automated machine learning user interface in Azure Machine Learning
Regression is a supervised machine-learning technique used to predict numeric values. Understand how to create regression models using Azure Machine Learning designer.
Learn how to train & publish a regression model with Azure Machine Learning designer
Classification is a supervised machine learning technique that requires classes or predicted categories. Understand how to create classification models using Azure Machine Learning designer.
Train & publish a classification model with Azure Machine Learning designer.
Clustering is an unsupervised machine-learning technique used to group similar entities based on their features. Understand how to create clustering models using Azure Machine Learning designer.
Train & publish a clustering model with Azure Machine Learning designer.
The Computer Vision service allows software engineers to create intelligent solutions extracting information from images, a common task in many artificial intelligence (AI) scenarios.
Learning how to use the Computer Vision cognitive service to analyze images
Image classification is a common workload in AI (artificial intelligence) applications. This harnesses the predictive power of machine learning, allowing AI systems to identify real-world items based on images.
Learning how to use the Custom Vision service to create an image classification solution.
Object detection is a form of computer vision in which AI (artificial intelligence) agents can identify & locate specific types of objects in an image or camera feed.
Learning how to use the Custom Vision service to create an object detection solution.
Face detection, analysis, & recognition are essential capabilities for AI (artificial intelligence) solutions. The face cognitive service in Azure makes it simple to integrate these capabilities into your applications.
Learning how to use the Face cognitive service to detect & analyze faces in images.
Optical character recognition (OCR) allows artificial intelligence (AI) systems to read the text in images, allowing the applications to extract information from photographs, scanned documents, & other sources of digitized text.
Learn how to read the text in images with the Computer Vision service
Processing invoices & receipts is a common task in many business scenarios. Organizations are turning to AI (artificial intelligence) to automate data extraction from scanned receipts.
Understand using the built-in receipt processing capabilities of the Form Recognizer service
Explore text mining & text analysis with the Language service's Natural Language Processing (NLP) features, including sentiment analysis, key phrase extraction, named entity recognition & language detection.
Learning how to use the Language service for text analysis
In this module, you will:
- Learn about speech recognition & synthesis
- Learning how to use the Speech cognitive service in Azure
Automated translation capabilities in an AI solution allow closer collaboration by removing language barriers.
After completing this module, you can perform text & speech translation using Azure Cognitive Services.
In this module, you'll:
- Learn what Conversational Language Understanding is.
- Learn about key features, such as intents & utterances.
- Build & publish a natural-language machine-learning model.
Bots are a popular way to provide support through multiple communication channels. The module describes how to use a knowledge base & Azure Bot Service to create a bot that answers user questions.
After finishing this module, you will be able to build a knowledge base with an Azure Bot Service bot.
Certification
This test is an opportunity to demonstrate knowledge of machine learning (ML) & artificial intelligence (AI) concepts & related Microsoft Azure services. Professionals for this exam should have familiarity with Exam AI-900's self-paced or instructor-led learning material.
This exam is intended for professionals with both technical & non-technical backgrounds. Data science & software engineering experience is not required; however, awareness of cloud basics & client server applications would be advantageous.
Azure AI Fundamentals is used to prepare for other Azure role-based certifications like Azure AI Engineer Associate or Azure Data Scientist Associate. Still, it is not a prerequisite for any of them.
If you pass this certification exam, you may be eligible for ACE college credit.
View the ACE college credit for certification tests for details
Skills measured
- The exam was updated on April 29, 2022, in the English language. Download the guide in the preceding "Tip" box for further details about the skills measured on this exam.
- Describing Artificial Intelligence workloads & considerations (20-25%)
- Describing basic principles of machine learning on Azure (25-30%)
- Describing features of computer vision workloads on Azure (15-20%)
- Detailing features of Natural Language Processing (NLP) workloads on Azure (25-30%)
Required exams: Microsoft Azure AI Fundamentals
FAQs
To become an azure admin, you must start with azure fundamentals. An individual with a professional experience in Azure-specific job roles can easily aim at improving their skills with official certification. However, you could also be included in other scenarios.
The Azure AI Fundamentals training is designed for anyone interested in understanding the types of solutions artificial intelligence (AI) makes possible & the services on Microsoft Azure that you can use to build them.
No! Even if you're from a non-technical background, our AI-900: Microsoft Certified Azure AI Fundamentals training requires no coding skills.
The migration Assistant tool helps the user to examine your IIS installation. It enables the user to recognize which site can be migrated to the cloud. It generally features components that must be relocated or supported on the Azure platform.
ASP.Net, PHP, & WCF are a type of web application that can be deployed with SQL Azure.
To attend the training session, you should have operational Desktops or Laptops with the required specification and a good internet connection to access the labs.
We recommend you attend the live session to practice & clarify the doubts instantly & get more value from your investment. However, if, due to some contingency, you have to skip the class, Radiant Techlearning will help you with the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption & NOT for distribution or commercial use.
Radiant Techlearning has a data center containing a Virtual Training environment for participants' hand-on-practice.
Participants can easily access these labs over the cloud with the help of a remote desktop connection.
Radiant virtual labs allow you to learn from anywhere in the world & in any time zone.
The learners will be enthralled as we engage them the real-world & industry Oriented projects during the training program. These projects will improve your skills & knowledge, & you will gain a better experience. These real-time projects will help you a lot in your future tasks & assignments.