Description
The AI-900: Microsoft Azure AI Fundamentals course introduces core concepts of Artificial Intelligence (AI) and the Microsoft Azure services used to build AI-powered solutions. Whether you’re new to the cloud or just curious about AI, this beginner-friendly course helps you understand real-world AI workloads and match them with the right Azure services.
It’s a blended learning format combining instructor-led training and Microsoft Learn modules. With hands-on labs, you’ll reinforce what you learn and explore topics deeper using the official Microsoft Learn platform.
If you’re planning to take the AZ-104 Microsoft Azure Administrator course next, AI-900 lays a strong conceptual foundation.
Who Should Take AI-900?
This course is ideal for:
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Anyone curious about AI and its business or technical applications.
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Students or professionals preparing for the Microsoft Certified: Azure AI Fundamentals exam.
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People interested in transitioning to roles in cybersecurity, data science, or AI.
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Beginners with no prior Azure or coding experience.
Prerequisites:
There are no official prerequisites for AI 900. However, you should have:
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Basic understanding of computers and the internet.
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Curiosity about how AI is used in industries.
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Willingness to explore through hands-on labs and exercises.
What You’ll Learn:
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Core principles of Artificial Intelligence.
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Concepts of machine learning, deep learning, and data processing.
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Overview of Azure services like Azure Machine Learning and Cognitive Services.
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Use cases including computer vision, NLP, and conversational AI.
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How to prepare for the AI 900 certification exam.
Course Format:
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Delivery: Online or In-Person (Melbourne)
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Duration: 1 day (with flexible scheduling)
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Includes: Hands-on labs, Microsoft Learn modules, real-world use cases
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Outcome: Prepares you for Microsoft Azure AI Fundamentals (AI 900) exam
Looking to expand your skills further? Check out our Microsoft Certification Courses.
Onsite Training for Teams
Need training for 3 or more team members? Ask us about custom onsite training. We’ll tailor the content for your organization, and deliver it at your location—saving you time and travel expenses.
Cancellation Policy:
If you need to cancel or reschedule, please notify us at least 10 days in advance.
Contact Us:
📞 0410 077 106
📧 fusman@technisaur.com.au
📍 Melbourne, VIC, Australia
You can also explore all our IT training courses for more learning options.
FAQs – Microsoft AI 900 Training
1. What is AI 900?
AI-900 is Microsoft’s Azure AI Fundamentals certification course, ideal for beginners who want to explore how AI works and how to use it with Azure services.
2. Is this course technical or beginner-friendly?
It’s beginner-friendly. You don’t need any programming or Azure background—just an interest in learning about AI.
3. Will I be certified after this course?
This course prepares you for the AI 900 certification exam. You’ll also receive a certificate of completion from Technisaur.
4. Can I take this course remotely?
Yes! We offer this course online as well as in-person at our Melbourne training center.
5. What’s the next step after AI 900?
You can move into more advanced certifications like AZ-104: Microsoft Azure Administrator or explore fields like Cybersecurity or Data Analytics.
6. Do I need prior Azure knowledge?
No, this course is designed for beginners with no previous Azure experience.
Modules
Module 1: Get started with AI on Azure
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.
Learning objectives
By the end of this module, you’ll be able to :
- In this module, you’ll learn about the kinds of solution AI can make possible and considerations for responsible AI practices.
Module 2 : Use Automated Machine Learning in Azure Machine Learning
Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the automated machine learning user interface in Azure Machine Learning
Module 3: Create a regression model with Azure Machine Learning designer
Regression is a supervised machine learning technique used to predict numeric values. Learn how to create regression models using Azure Machine Learning designer.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to train and publish a regression model with Azure Machine Learning designer.
Module 4 : Create a classification model with Azure Machine Learning designer
Classification is a supervised machine learning technique used to predict categories or classes. Learn how to create classification models using Azure Machine Learning designer.
Learning objectives
By the end of this module, you’ll be able to :
- Train and publish a classification model with Azure Machine Learning designer
Module 5: Create a clustering model with Azure Machine Learning designer
Clustering is an unsupervised machine learning technique used to group similar entities based on their features. Learn how to create clustering models using Azure Machine Learning designer.
Learning objectives
By the end of this module, you’ll be able to :
- Train and publish a clustering model with Azure Machine Learning designer
Module 6 : Analyze images with the Computer Vision service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the Computer Vision cognitive service to analyze images.
Module 7: Classify images with the Custom Vision service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the Custom Vision service to create an image classification solution.
Module 8 : Detect objects in images with the Custom Vision service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the Custom Vision service to create an object detection solution.
Module 9: Detect and analyze faces with the Face service
Face detection, analysis, and recognition are important capabilities for artificial intelligence (AI) solutions. The Face cognitive service in Azure makes it easy integrate these capabilities into your applications.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the Face cognitive service to detect and analyze faces in images.
Module 10 : Read text with the Computer Vision service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to read text in images with the Computer Vision service
Module 11 : Analyze receipts with the Form Recognizer service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the built-in receipt processing capabilities of the Form Recognizer service
Module 12 : Analyze text with the Language service
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.
Learning objectives
By the end of this module, you’ll be able to :
- Learn how to use the Language service for text analysis
Module 13 : Recognize and synthesize speech
Learn how to recognize and synthesize speech by using Azure Cognitive Services.
Learning objectives
By the end of this module, you’ll be able to :
- Learn about speech recognition and synthesis
- Learn how to use the Speech cognitive service in Azure
Module 14 : Translate text and speech
Automated translation capabilities in an AI solution enable closer collaboration by removing language barriers.
Learning objectives
By the end of this module, you’ll be able to :
- After completing this module, you will be able to perform text and speech translation using Azure Cognitive Services.
Module 15 : Create a language model with Conversational Language Understanding
In this module, we’ll introduce you to Conversational Language Understanding, and show how to create applications that understand language.
Learning objectives
By the end of this module, you’ll be able to :
- Learn what Conversational Language Understanding is.
- Learn about key features, such as intents and utterances.
- Build and publish a natural-language machine-learning model.
Module 16 : Build a bot with the Language Service and Azure Bot Service
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.
Learning objectives
By the end of this module, you’ll be able to :
- After completing this module, you’ll be able to create a knowledge base with an Azure Bot Service bot.
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