Introduction to Microsoft Azure AI Fundamentals
Develop the skills necessary to kickstart a career in machine learning and artificial intelligence using Azure services with this online course from Microsoft.
Duration
5 weeks
Weekly study
4 hours
100% online
How it works
Unlimited subscription
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This course has been created in partnership with Microsoft. |
Artificial intelligence has turned science fiction into a reality, creating almost limitless technological possibilities.
On this five-week course, you’ll learn how AI can improve apps, advance technology, and develop solutions. With this knowledge, you’ll be ready to take the AI-900 exam and open the door to a career in artificial intelligence.
AI has enabled incredible advances in sectors from healthcare to environmental protection.
On this course, you’ll examine machine learning processes, from anomaly detection to knowledge mining. You’ll learn how to use Azure Machine Learning designer to perform automated machine learning techniques and discover their real-world applications.
With this knowledge, you’ll be able to develop AI solutions to theoretical and real-life problems.
Computer Vision allows software systems to see the world through images and video. Using the Computer Vision service, you’ll learn how to detect objects, classify images, and read text.
Azure’s Language service has a range of tools that allow you to improve your applications’ accessibility and communication with users.
You’ll learn how Azure tools can translate text, synthesize speech, and create language models, finishing by learning to create a bot that can answer user questions.
By the end of this course, you’ll understand how to use Azure services to assist your AI processes and be ready to take the AI-900 exam, demonstrating your knowledge of AI and machine learning.
With AI, we can build solutions that seemed like science fiction a short time ago; enabling incredible advances in health care, financial management, environmental protection, and other areas to make a better world for everyone.
Simply put, AI is the creation of software that imitates human behaviors and capabilities. Let's learn about the key workloads of AI.
At Microsoft, AI software development is guided by a set of six principles, designed to ensure that AI applications provide amazing solutions to difficult problems without any unintended negative consequences.
In this activity, you will learn how to use automated machine learning in Azure Machine Learning.
In this activity, you will learn about creating a regression model with Azure Machine Learning designer
In this activity you will learn how to create a classification model with Azure Machine Learning designer.
In this activity, you will learn how to create a clustering model with Azure Machine Learning designer.
The Computer Vision service enables software engineers to create intelligent solutions that extract information from images; a common task in many artificial intelligence (AI) scenarios.
Image classification is a common workload in artificial intelligence (AI) applications. It harnesses the predictive power of machine learning to enable AI systems to identify real-world items based on images.
Object detection is a form of computer vision in which artificial intelligence (AI) agents can identify and locate specific types of object in an image or camera feed.
Face detection, analysis, and recognition is an important capability for artificial intelligence (AI) solutions. The Face cognitive service in Azure makes it easy integrate these capabilities into your applications.
Optical character recognition (OCR) enables artificial intelligence (AI) systems to read text in images, enabling applications to extract information from photographs, scanned documents, and other sources of digitized text.
Processing invoices and receipts is a common task in many business scenarios. Increasingly, organizations are turning to artificial intelligence (AI) to automate data extraction from scanned receipts.
Explore text mining and text analysis with the Language service's natural language processing (NLP) features, which include sentiment analysis, key phrase extraction, named entity recognition, and language detection.
Learn how to recognize and synthesize speech by using Azure Cognitive Services.
Automated translation capabilities in an AI solution enable closer collaboration by removing language barriers.
In this module, we'll introduce you to Conversational Language Understanding, and show how to create applications that understand language.
Bots are a popular way to provide support through multiple communication channels. This module describes how to use a knowledge base and Azure Bot Service to create a bot that answers user questions.
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