AI-900T00 Introduction to AI in Azure
This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform. The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.
- Understand AI Fundamentals – Core concepts and types of AI workloads
- Responsible AI – Principles for ethical AI development and deployment
- Azure AI Services – Overview of Microsoft Azure AI offerings
- AI Workloads – Machine learning, computer vision, NLP, generative AI
- Hands-on Practice – Explore Azure AI services via Microsoft Learn labs
- Certification Prep – Build knowledge to prepare for the AI-900 exam
The Introduction to AI in Azure course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.
Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically:
- Experience using computers and the internet.
- Interest in use cases for AI applications and machine learning models.
- A willingness to learn through hands-on experience
- Core AI concepts: generative AI, computer vision, speech, NLP, data and insights, Responsible AI
- Fundamentals of machine learning: regression, classification, clustering, deep learning, transformers
- Module assessment
- Problem definition and data preparation
- Model training and integration
- Model monitoring and lifecycle management
- Module assessment
- How language models and transformers work
- Differences across language models
- Prompt engineering for better results
- Responsible generative AI practices
- Generative AI use cases and applications on Azure
- Module assessment
- NLP fundamentals: statistical and semantic models
- Azure AI Language: text analytics and conversational AI
- Azure AI Translator capabilities
- Getting started with NLP in Azure AI Foundry
- Module assessment
- Concepts: speech recognition, synthesis, and translation
- Using Azure AI Speech APIs and services
- Module assessment
- Vision concepts: image processing, ML for vision, modern vision models
- Azure AI Vision capabilities: image analysis and face recognition
- Vision services in Azure AI Foundry portal
- Module assessment
- Concepts: extracting data from images, forms, multimodal inputs
- Azure AI Document Intelligence and Content Understanding
- Knowledge mining with Azure AI Search
- Module assessment
- Guided practice across generative AI, NLP, speech, vision, and information extraction services
- Module assessments for each major area