In this AI-900 Study Guide, I will share both free and paid options, whether books, video training, or simply links to articles and blog posts.
Watch the AI-900 Study Guide Microsoft Azure AI Fundamentals Video. 👇🏾
AI-900 Microsoft Learning Path
Don’t miss these free, self-paced online resources to help you gain the skills needed to earn your certification. AI-900 online learning paths.
AI-900 Instructor-led training (Microsoft Official Courses)
This course introduces fundamental 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 (https://azure.com/learn). 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. $550 Course AI-900T00: Microsoft Azure AI Fundamentals
AI-900 Video Training
This learning path is designed to help you prepare for the AI-900 Microsoft Azure AI Fundamentals. $35 monthly subscription A Cloud Guru AI-900: Microsoft Certified Azure AI Fundamentals
AI-900 Practice Exams
Microsoft Official Practice Tests are self-study tools that prepare candidates for the Microsoft required exams. $99.00 - $109.00 Microsoft Official Practice Test Fundamentals - Microsoft Official Practice Test
Another practice test and sample questions. Free Examtopics.com Microsoft AI-900 Exam
Audience Profile for the Exam
This exam is an opportunity to demonstrate knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services. Candidates for this exam should have familiarity with AI-900’s self-paced or instructor-led learning material.
About Exam AI-900: Microsoft Azure AI Fundamentals
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, awareness of cloud basics and client-server applications would be beneficial.
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it is not a prerequisite for any of them.
For the full list of the skills that the exam measures, along with the level of experience and expertise that you’ll need as an exam candidate, check out the Skills measured document.
This section itemizes the topics covered in the Exam Prep session and links to Microsoft documentation so you can review the topics in detail.
Describe Artificial Intelligence workloads and considerations (20-25%)
Describe fundamental principles of machine learning on Azure (25-30%)
Describe features of computer vision workloads on Azure (15-20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%)
Describe AI workloads and considerations (15–20%)
Identify Features of Common AI Workloads
AI in Microsoft azure
Identify guiding principles for responsible AI
Describe fundamental principles of machine learning on Azure (30–35%)
Identify common machine learning types
Describe core machine learning concepts
Features and labels in a dataset
Identify core tasks in creating a machine learning solution
Describe capabilities of no-code machine learning with Azure Machine Learnin
Describe features of Computer Vision workloads on Azure (15–20%)
Identify common types of Computer Vision solution
Overview of Computer Vision
Identify Azure tools and services for Computer Vision tasks
Describe features of natural language processing (NLP) workloads on Azure (15–20%)
Identify features of common NLP workload scenarios
Identify Azure tools and services for NLP workloads
Describe features of conversational AI workloads on Azure (15–20%)
Identify common use cases for conversational AI
Identify Azure services for conversational AI