Microsoft Certified: Azure AI Fundamentals: AI-900: Azure AI Fundamentals
Certification Exam:
- 15 Courses | 19h 37m 21s
- Includes Test Prep
- 2 Courses | 1h 17m
- 1 Book | 1h 47m
Explore machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services as you prepare for the AI-900:Azure AI Fundamentals certification exam.
GETTING STARTED
Azure AI Fundamentals: Azure Machine Learning Fundamentals
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1m 5s
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6m 59s
GETTING STARTED
Azure AI Fundamentals: Artificial Intelligence & Machine Learning
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1m 21s
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5m 42s
COURSES INCLUDED
Azure AI Fundamentals: Azure Machine Learning Fundamentals
Artificial intelligence (AI) and machine learning (ML) seem to be everywhere we look, and with each passing day, there are new breakthroughs in AI/ML technology. In this course, you will explore key features and uses of AI and ML, computer vision in Azure, and natural language processing (NLP) in Azure. Then you will discover the purpose of knowledge mining in Azure, investigate document intelligence in Azure, and examine generative AI in Azure. Finally, you'll delve into ethical considerations for AI, challenges and risks associated with AI, and critical considerations for the design and implementation of responsible AI. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
12 videos |
1h 6m
Assessment
Badge
Azure AI Fundamentals: Artificial Intelligence Concepts
Artificial intelligence (AI) and machine learning (ML) are expansive concepts that mean different things to different people. With a vast and ever-growing list of practical applications for AI/ML, it is no surprise that the technology is garnering the attention of organizations far and wide. In this course, you will explore key concepts of AI, beginning with ML types. Then you will discover data in ML, labeled and unlabeled data, and data features. Next, you will delve into key methods and techniques, such as regression, binary classification, multi-class classification, and clustering. Finally, you will focus on the features, advantages, and disadvantages of supervised and unsupervised learning, and the purpose of deep learning. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
12 videos |
1h 2m
Assessment
Badge
Azure AI Fundamentals: Artificial Intelligence Principles
Artificial intelligence (AI) and machine learning (ML) are solving a significant number of business and social problems and giving computers a new way to handle and process vast amounts of data. In this course, you'll learn about AI principles, beginning with fairness, reliability, and safety in AI algorithms, privacy and security for responsible AI, and inclusiveness, transparency, and accountability in AI algorithms. Then you'll dig into Azure AI's capabilities, Machine Language Operations (MLOps), Azure AI model management, and Azure AI model training. Finally, you'll explore key concepts surrounding Azure AI content safety and Azure reinforcement learning. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
14 videos |
1h 25m
Assessment
Badge
Azure AI Fundamentals: Machine Learning with Azure AI
Azure Machine Learning Studio is part of a suite of services that facilitates machine learning (ML) by providing a single interface for building, managing, deploying, testing, and collaborating. In this course, you will discover Azure AI and ML services, beginning with the features and capabilities of Azure Machine Learning Studio and Azure OpenAI Studio. Then you will dig into how to create an Azure Machine Learning Studio account and Azure AI service resources. Next, you will investigate Azure AI services, authentication for Azure AI services, and Azure ML workloads. Finally, you will explore compute resources, dataset management, and pipeline management. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
16 videos |
1h 31m
Assessment
Badge
Azure AI Fundamentals: Introduction to Azure Machine Learning Studio
The Azure Machine Learning Studio provides a proficient design tool that can be used to build machine learning pipelines. In this course, you'll explore Azure Machine Learning Studio and practice using its features for managing, normalizing, and transforming data for use in regression, classification, and clustering models. You'll begin with Azure service experiments, classification evaluation metrics, and regression evaluation metrics. Then, you'll learn how to create an Azure Machine Learning workspace, how to create a compute resource, and how to create a dataset. Finally, you'll discover how to create model packages and how to deploy models. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
10 videos |
54m
Assessment
Badge
Azure AI Fundamentals: Working with Azure Machine Learning Studio
Azure Machine Learning Studio can be used to build machine learning pipelines and manage, normalize, and transform data for use in regression, classification, and clustering models. In this course, you will work with Azure Machine Learning Studio, beginning with ingesting data from Azure storage and Azure Blob storage, labeling data in Azure Machine Learning Studio, running and testing scripts, and creating an automated model. Then you will discover how to run an automated experiment, select the best model, deploy a model as a predictive service, and test a predictive service. Finally, you will explore how to manage compute resources and data stores, manage datasets and experiments, pipelines and models, and endpoints. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
15 videos |
1h
Assessment
Badge
Azure AI Fundamentals: Using Azure Machine Learning Designer
Azure Machine Learning Studio and Designer provide powerful options for authoring machine learning (ML) models. In this course, you'll explore model authoring with Azure Machine Learning Designer, including how to work with datasets, select dataset features, and add data transformations. Then, you'll discover how to normalize data, view normalized data, and split datasets. Finally, you'll explore how to use regression, classification, and clustering models in Azure Machine Learning Designer. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
12 videos |
1h 4m
Assessment
Badge
Azure AI Fundamentals: Evaluating Models in Azure AI
In order to build a useful machine learning deployment, you must be able to evaluate and verify the AI model and data, as well as the accuracy and effectiveness of its predictions. Azure Machine Learning Studio and the designer provide multiple easy-to-use methods for evaluating and scoring a model. In this course, you will learn how to score and evaluate models, how to run pipelines, and how to analyze evaluation output. Then you will dig into evaluation results, visualizing data in a scoring model, assessing regression model results, and investigating classification model results. Finally, you will explore clustering model results, inference pipelines, web service output, and predictive service deployment. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
16 videos |
1h 35m
Assessment
Badge
Azure AI Fundamentals: Azure Data Explorer
Azure Data Explorer provides powerful, tools for fast, real-time data exploration and analysis. In this course, you'll explore key concepts of Azure Data Explorer, including clusters, databases, tables, and data ingestion. First, learn how to efficiently ingest structured, semi-structured, and unstructured data. Then, dive into mastering Kusto Query Language (KQL), starting with basic queries for AI-driven data analysis and progressing to advanced techniques for extracting deeper insights. Use Azure Data Explorer for real-time data analysis and AI-driven insights and create dashboards and visualizations for AI model insights. Learn the skills to handle large-scale data sets and perform complex analytics using KQL. Finally, outline role-based access control (RBAC) and security best practices for managing data in Azure Data Explorer. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
13 videos |
1h 18m
Badge
Azure AI Fundamentals: Azure Natural Language Processing
A powerful feature of machine learning is natural language processing (NLP). NLP allows computers to identify and process natural language and can be used for speech to text and text to speech processing, sentiment analysis, and translation. In this course, you'll learn about NLP in Azure, use cases for NLP, the Azure AI language service, and the Azure AI speech service. Then you'll explore working with Azure Text Analytics, key phrase extraction, named entity recognition (NER), and sentiment analysis and opinion mining. Finally, you'll discover how to train a language model, features of the Azure AI Translator Service, how to translate text, and how to translate speech. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
14 videos |
1h 24m
Assessment
Badge
Azure AI Fundamentals: Creating a Conversational AI Bot
Conversational bots are a powerful tool that can interact and respond to queries very much like a human would. They can also be used as knowledge bases. In this course, you'll learn about conversational AI bot creation, beginning with conversational bot use cases, and how to create, populate, train, publish, and test a knowledge base. Then you'll delve into creating a bot, extending a bot framework, testing a bot, application insights, and how to publish a bot. Finally, you'll learn how to connect bots to standard channels and connect an application to a bot, and how to create, deploy, and test a virtual assistant. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
17 videos |
1h 44m
Assessment
Badge
Azure AI Fundamentals: Introduction to Azure AI Vision
Computer vision is the machine learning capability to allow computers to "see" in a similar manner to how a person can see. In this course, you'll be introduced to Azure AI Vision, beginning with images and image processing considerations, an introduction to the Azure AI Vision service and the Azure AI Custom Vision service. Then you'll learn about Azure image analysis, the Azure Face service, Azure video analysis, and Azure AI image classification. Finally, you'll explore Azure AI object detection, be introduced to Azure AI Vision Studio, and discover how to get started with Azure AI Vision Studio. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
13 videos |
1h 21m
Assessment
Badge
Azure AI Fundamentals: Getting Started with Azure AI Vision
Azure AI Vision unleashes your ability to identify, distinguish, and interpret objects, people, and even text from images or video. In this course you will explore Azure AI Vision, beginning with analyzing images, describing and tagging images, and training a classifier model. Then you will discover how to evaluate a classifier model, deploy and test a prediction model, and train an object detection model. Next, you will learn how to evaluate an object detection model and use a model as a service. Finally, you will investigate semantic segmentation. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
11 videos |
1h 4m
Assessment
Badge
Azure AI Fundamentals: Working with AI Vision
Computer vision allows computers to 'see', and identify, distinguish, and interpret objects, people, and text from images or video. In this course, you will continue to work with Azure AI Vision, beginning with facial detection and analysis and the Azure AI Video Indexer service. Then you will discover key aspects of face and age detection and find out how to identify faces in videos. Next, you will learn how to use Face service to detect and analyze faces and verify. Finally, you will investigate Azure AI vision Spatial Analysis and work with the Spatial Analysis container. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
12 videos |
1h 8m
Assessment
Badge
Azure AI Fundamentals: Azure Document & Optical Character Recognition
A powerful feature of computer vision is the ability to detect, identify, and even analyze meaningful information from various sources. In this course, you'll learn about Azure AI's document and optical character recognition (OCR) services, beginning with key features of the Azure Optical Character Recognition API and how to read text from various sources, including photographs and digitized documents. Then you'll explore the Azure Document Intelligence Service and how to work with Azure AI Document Intelligence. Finally, you'll delve into the Read API, the pre-built receipt model, the customer form recognizer model, how to identify fields on a receipt, and how to process tables in scanned forms. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
14 videos |
1h 24m
Assessment
Badge
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COURSES INCLUDED
Azure AI Fundamentals: Artificial Intelligence & Machine Learning
Artificial Intelligence and machine learning in particular are solving a significant number of business and social problems and giving computers a new way to handle and process vast amounts of data. In this course, you'll learn about AI and machine learning concepts regarding regression, classification, and clustering algorithms. You'll explore how to manage datasets and work with labeled versus unlabeled data. You'll learn how supervised and unsupervised machine learning can be used, as well as how to build and use AIs safely, transparently, and fairly. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
18 videos |
1h 43m
Assessment
Badge
Azure AI Fundamentals: Machine Learning with Azure Services
Azure ML provides a suite of services to help with machine learning by providing a single interface to build, manage, deploy, test, and collaborate via the Azure Machine Learning Studio. In this course, you'll learn about the Azure ML services provided, including as Machine Learning designer and automated machine learning. You'll explore how to access and use the Azure Machine Learning Studio and review the Machine Learning features available in the service. In particular, you'll learn about the features of the Computer Vision, Custom Vision, Face, and Form Recognizer services. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
18 videos |
1h 50m
Assessment
Badge
Azure AI Fundamentals: Using Azure Machine Learning Studio
The Azure Machine Learning Studio is a complete web tool and graphical user interface for building, managing, deploying, evaluating, and testing machine learning algorithms and workloads from initial design to final deployment. In this course, you'll investigate the different features of the Azure ML Studio interface and use it to create datasets, ingest data, create models automatically, build prediction services, and finally, manage endpoints for a machine learning model. Furthermore, you'll explore the datastores, compute resources, experiments, pipelines, and model management interfaces that are utilized when working with Azure ML Studio. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
18 videos |
1h 29m
Assessment
Badge
Azure AI Fundamentals: Authoring with the Azure ML Studio Designer
The Azure Machine Learning Studio provides a proficient designer that can be used to build machine learning pipelines. In this course, you'll explore Azure ML Studio Designer and practice using its features for managing, normalizing, and transforming data for use in regression, classification, and clustering models. You'll also learn how to select features from a dataset and create datasets for training and validating models within Studio Designer. By the end of the course, you'll be able to use datasets, add transformations, normalize and clean data, split datasets, and configure and use a number of models, all within Azure ML Studio Designer. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
11 videos |
1h 10m
Assessment
Badge
Azure AI Fundamentals: Evaluating Models with the ML Designer
In order to build a powerful and useful machine learning deployment, you must be able to evaluate and verify the AI model and data, as well as the accuracy and effectiveness of its predictions. Azure Machine Learning Studio and the Designer provide multiple easy-to-use methods for evaluating and scoring a model. In this course, you'll learn how to score and evaluate models and interpret and evaluate the results from some common models. You'll also explore how to create an inference pipeline, add web service output to provide external access to the model, and deploy and test a predictive web service. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
16 videos |
2h 2m
Assessment
Badge
Azure AI Fundamentals: Anomaly Detection
Anomaly detection can be a critical part of almost any business and can be used for fraud detection, identifying failures, and noticing unusual patterns in logs, records, or any time series based data. In this course, you'll learn the purpose and uses for anomaly detection and how AI anomaly detection can be used to identify unusual patterns, failures, and fraud. You'll then learn about the challenges of detecting anomalies in real world situations and how AI-based anomaly detection can be used to mitigate those challenges. Finally, you'll learn how to build, configure, deploy, and test the Azure Anomaly Detection service to create anomaly detection services you can use in real world scenarios. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
12 videos |
1h 27m
Assessment
Badge
Azure AI Fundamentals: Natural Language Processing
A powerful feature of machine learning is Natural Language Processing. Natural language processing allows computers to identify and process natural language and can be used for speech-to-text and text-to-speech processing, sentiment analysis, and translation. In this course, you'll learn about the features, uses, and challenges of NLP and the Azure services supporting NLP. You'll also explore intents and entities. In particular, you'll learn to train models using the Azure services for text analytics, speech-to-text, text-to-speech, sentiment analysis, and translation. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
11 videos |
1h 5m
Assessment
Badge
Azure AI Fundamentals: Conversational AI Bot
Conversational bots are becoming a powerful tool for businesses since they can interact and respond to queries and questions similar to how a real person would. However, they are not limited to this use and can also become personal digital assistants and be used as knowledgebases. In this course, you'll learn about the QnA Maker for knowledgebase bots, how to create a conversational bot, how to connect the bot to external channels and apps, and even how to create a simple personal digital assistant. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
17 videos |
2h 1m
Assessment
Badge
Azure AI Fundamentals: Computer Vision
Computer vision is the machine learning capability to allow computers to "see" similar to how a person can see, and be able to identify, distinguish, and interpret objects, people, and even text from images or video. In this course you will learn about the Azure ML Computer Vision service, Computer Vision Models, and how it can be trained and used to detect and classify objects in images and videos using a Classifier model and semantic segmentation. You'll also learn how to evaluate the results of an object detection model. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
15 videos |
1h 22m
Assessment
Badge
Azure AI Fundamentals: Face & Optical Character Recognition
An advanced and powerful feature of computer vision is the ability to detect, identify, and even analyze faces and forms in images and videos. In this course, you'll learn how to use the Azure Face Detection service and Computer Vision service to determine a person's age from an image and to determine their sentiment. You'll also explore how to use the Form Recognizer service to read and process forms using Optical Character Recognition. Finally, you'll learn how to use the Receipt and Custom Form Recognizer to process fields from receipts. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
16 videos |
1h 54m
Assessment
Badge
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EARN A DIGITAL BADGE WHEN YOU COMPLETE THESE COURSES
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.BOOKS INCLUDED
Book
Microsoft Azure AI Fundamentals Certification Companion: Guide to Prepare for the AI-900 ExamPrepare for the Azure AI Fundamentals certification examination. This book covers the basics of implementing various Azure AI services in your business. The book not only helps you get ready for the AI-900 exam, but also helps you get started in the artificial intelligence (AI) world.
1h 47m
By Krunal S. Trivedi
SKILL BENCHMARKS INCLUDED
Azure AI Fundamentals: Artificial Intelligence on Microsoft Azure Competency (Intermediate Level)
The Artificial Intelligence on Microsoft Azure Competency benchmark measures your ability to recall and identify the features of common AI workloads and principles for responsible AI implementation. A learner who scores high on this benchmark demonstrates that they have the necessary knowledge of AI workloads on the Azure platform.
15m 59s
| 16 questions
Azure AI Fundamentals: Conversational AI on Microsoft Azure Competency (Intermediate Level)
The Conversational AI on Microsoft Azure Competency benchmark measures your ability to recall and identify the common use cases for conversational AI, Azure tools, and services for conversational AI. A learner who scores high on this benchmark demonstrates that they have the necessary knowledge and skills to build conversational AI workloads on the Azure platform.
15m
| 15 questions
Azure AI Fundamentals: Natural Language Processing on Microsoft Azure Competency (Intermediate Level)
The Natural Language Processing on Microsoft Azure Competency benchmark measures your ability to recall and identify the common NLP workloads, and Azure tools and services for NLP workloads. A learner who scores high on this benchmark demonstrates that they have the necessary knowledge and skills to build NLP workloads on the Azure platform.
9m
| 9 questions
Azure AI Fundamentals: Machine Learning on Microsoft Azure Competency (Intermediate Level)
The Machine Learning on Microsoft Azure Competency benchmark measures your ability to recall and identify common machine learning types, core machine learning concepts such as identifying features and labels in a dataset, core tasks in creating machine learning solutions, and capabilities of no-code machine learning with Azure Learning Studio. A learner who scores high on this benchmark demonstrates that they have the necessary knowledge and skills to build machine learning solutions on the Azure platform.
23m
| 23 questions
Azure AI Fundamentals: Computer Vision on Microsoft Azure Competency (Intermediate Level)
The Computer Vision on Microsoft Azure Competency benchmark measures your ability to recall and identify the common types of computer vision solutions, and Azure tools and services for computer vision tasks. A learner who scores high on this benchmark demonstrates that they have the necessary knowledge and skills to build computer vision solutions on the Azure platform.
18m
| 18 questions
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