AI-900: Microsoft Azure AI Fundamentals
Prepare to earn the Microsoft Azure AI Fundamentals certification in just 3 hours a week! Next cohort starts March 4, 2025!
Why Hybrid Training?
Flexible Hybrid Format
Experience the perfect blend of live instruction and self-paced learning, allowing you to stay engaged without disrupting your schedule.
Hands-On Learning
Gain practical experience through assignments, simulations, and labs, all designed to prepare you for real-world applications.
Consistent Instructor Support
Enjoy weekly live sessions that provide direct access to expert guidance, feedback, and support.
Certification Preparation
Prepare to earn Microsoft validated certifications that validate your skills, making you more attractive to career-focused employers.
Course Description
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..
Audience Profile
The Azure AI Fundamentals 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.
About this Course
Course Outline
Skills at a glance
Describe Artificial Intelligence workloads and considerations (15–20%)
Describe fundamental principles of machine learning on Azure (20–25%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
Describe features of generative AI workloads on Azure (15–20%)
Describe Artificial Intelligence workloads and considerations (15–20%)
Identify features of common AI workloads
Identify features of content moderation and personalization workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify document intelligence workloads
Identify features of generative AI workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
Describe fundamental principles of machine learning on Azure (20–25%)
Identify common machine learning techniques
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Identify features of deep learning techniques
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe Azure Machine Learning capabilities
Describe capabilities of automated machine learning
Describe data and compute services for data science and machine learning
Describe model management and deployment capabilities in Azure Machine Learning
Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Describe capabilities of the Azure AI Vision service
Describe capabilities of the Azure AI Face detection service
Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Describe capabilities of the Azure AI Language service
Describe capabilities of the Azure AI Speech service
Describe features of generative AI workloads on Azure (15–20%)
Identify features of generative AI solutions
Identify features of generative AI models
Identify common scenarios for generative AI
Identify responsible AI considerations for generative AI
Identify capabilities of Azure OpenAI Service
Describe natural language generation capabilities of Azure OpenAI Service
Describe code generation capabilities of Azure OpenAI Service
Describe image generation capabilities of Azure OpenAI Service
Duration
4 Weeks
Prerequisites
none
Level
Beginner
Product
Microsoft Azure
Role
Administrator
Hybrid Course Schedule
| Course | Start Date | End Date | Meets on | Start Time | End Time | Time Zone | Weeks | Weekly Live Training | Weekly Self Paced |
|---|---|---|---|---|---|---|---|---|---|
| AI-900: Azure AI Fundamentals | March 4th | April 8th | Tuesday | 12:00 PM | 1:00 PM | Central | 4 | 1 Hour | 2 Hours |
| AI:102 Designing and Implementing a Microsoft Azure AI Solution | April 15th | June 4th | Tuesday | 12:00 PM | 1:00 PM | Central | 8 | 1 Hour | 2 Hours |
Microsoft Azure AI Engineer Track
Azure AI Fundamentals
Start Date: March 4, 2025
Duration: 4 Weeks
Format: Live + On-demand
Price: $299
View Course Description
Azure AI Engineer
Start Date: April 15, 2025
Duration: 8 Weeks
Format: Live + On-demand
Price: $699
View Course Description
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