Exam AI-900: Microsoft Azure AI Fundamentals Crash Course
Published by Pearson
Accelerate Your Certification Success with Azure AI Essentials
- Gain clarity on essential Azure AI concepts through structured, real-world examples.
- Confidently prepare to pass Exam AI-900 and achieve Microsoft AI certification.
- Explore Azure AI in an engaging, accessible, and stress-free learning environment.
Artificial Intelligence (AI) is the capability of a computer to imitate human behavior. Microsoft Azure includes a suite of tools that enable AI engineers to ingest data, build machine learning (ML) models, and deploy those models as REST API web services. Azure also includes a number of platform-as-a-service cognitive services that give Azure developers easy access to pre-trained ML models.
Because AI/ML factor into most customer-facing software nowadays, coupled with the Azure AI/ML tools' steep learning curve, this training presents an excellent opportunity for IT professionals to learn the technology in a clear, low-stress manner.
Specifically, this Crash Course covers the objectives for Microsoft Exam AI-900: Microsoft Azure AI Fundamentals. This exam fulfills the requirements of the Microsoft Certified AI Fundamentals certification.
Note that Microsoft considers their 900-series exams to be beginner-to-intermediate level skill sets. The certification is intended for both technical and non-technical audiences, and covers the Azure AI skills from a mostly theoretical viewpoint.
What you’ll learn and how you can apply it
- Common Azure AI workloads, including computer vision, natural language processing, and generative AI.
- Core machine learning concepts and scenarios in Azure, including deep learning techniques and Azure Machine Learning Studio capabilities.
- Azure AI tools and services tailored for computer vision, NLP, speech processing, and generative AI solutions.
- Responsible AI principles, including fairness, inclusivity, privacy, transparency, and accountability in Azure AI solutions.
- Confidence to pass the Microsoft AI-900 certification exam.
This live event is for you because...
- Azure AI certification candidates
- Future, present, or future data scientists or AI/ML engineers
- Azure professionals who will support Azure AI/ML projects
- Non-technical professionals who need to understand a bit of how Azure AI works
Prerequisites
- The AI-900 is supposed to be a beginner/fundamentals skill set. Thus, the core prerequisite is that the learner has intermediate knowledge of Azure from any job role: administrator, developer, architect, business analyst, etc.
- Ideally the learner is already a data scientist with Python, Scala, or R programming knowledge, but I'll teach to any level.
Course Setup
- Windows or macOS computer
- Web browser and Internet connection
- Microsoft account to create an Azure trial subscription (free)
- Microsoft Azure 30-day trial (free)
If the learner wants to dive in and actually practice the skills, he or she should also have:
- A paid Azure subscription if they already used their trial
- Visual Studio 2019 (the free Community edition is fine)
- Visual Studio Code (free)
- Azure Command-Line Interface (CLI) (free)
- Docker Desktop software (free)
- The course files will be available at Tim's GitHub repository
Recommended Preparation
- Read: Machine Learning with Python for Everyone, by Mark Fenner (book)
- Read: Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications, First Edition, by Andrew Kelleher and Adam Kelleher (book)
Recommended Follow-up
- Watch: Ref AZ-900: Microsoft Azure Fundamentals, 3rd Ed, by Jim Cheshire (video)
- Watch: Linux on Azure and LFCS Certification, by Sander van Vugt (video)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Segment 1: Introduction and AI Fundamentals (60 mins)
- Welcome & Introduction
- Identify features of common AI workloads
- Describe responsible AI principles
- Q&A and Review
Break (9 mins)
Segment 2: Core Machine Learning Concepts (60 mins)
- Identify common machine learning techniques
- Describe Azure Machine Learning capabilities
- Q&A and Review
Break (9 mins)
Segment 3: Azure Computer Vision Solutions (60 mins)
- Identify common computer vision scenarios
- Describe facial detection and analysis features
- Explore Azure AI Vision and Face services
- Q&A and Review
Break (9 mins)
Segment 4: NLP and Speech Processing with Azure (60 mins)
- Identify NLP workload scenarios
- Describe Azure speech solutions
- Overview Azure AI Language and Speech services
- Q&A and Review
Break (9 mins)
Segment 5: Generative AI and Azure OpenAI Service (60 mins)
- Describe generative AI workloads and scenarios
- Explore Azure OpenAI Service capabilities
- Responsible AI considerations for generative AI
- Final Q&A, Review, and Next Steps
Your Instructor
Tim Warner
Tim Warner has been a Microsoft MVP in Azure AI and Cloud/Datacenter Management for 6 years and a Microsoft Certified Trainer for more than 25 years. His O'Reilly Live Training classes on generative AI, GitHub, DevOps, data engineering, cloud computing, and Microsoft certification reach hundreds of thousands of students around the world. He's written for Microsoft Press, presented at Microsoft Ignite, and contributed to several Microsoft open-source projects. You can connect with Tim on LinkedIn: timw.info/li.