I just get my AI-900 Microsoft AI Fundamentals certification and it is time now to share my preparation notes for those who are interested to pass the “Microsoft Azure AI Fundamentals” exam and get certified.
This article is just one another preparation guide to Microsoft exam AI-900 but I hope you will find it useful 🙂
Even you don’t plan to take the exam, all this content is really interesting to read and understand if you want to discover and improve your knowledge on the Microsoft AI Platform. You will find below more than XXX slides, good articles, nice courses and excellent tutorials
Audience Profile : This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required.
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’s not a prerequisite for any of them.
Before starting studying, you must know very well what this certification is about and what are the prerequisites.
The topics included in this exam are the following :
- Describe AI workloads and considerations (15-20%)
- Describe fundamental principles of machine learning on Azure (30-35%)
- 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 conversational AI workloads on Azure (15-20%)
The exam length is one hour. There are 63 questions and you need 700 points min over 1000 to pass the exam (like all other Microsoft exams).
First place to go is the Microsoft Learn platform where a dedicated learning path is available for free !!
Microsoft Certified: Azure AI Fundamentals – Learning Path https://docs.microsoft.com/en-us/learn/certifications/azure-ai-fundamentals
I use this content to structure this preparation guide, I synthesize what I think is mandatory to know and I have additional lectures, articles and training resources
Module 1 – Describe AI workloads and considerations (15-20%)
Get started with artificial intelligence on Azure
Machine Learning Solution Pitch deck ==> really good deck to prepare this module
Anomaly Detector : An AI service that helps you foresee problems before they occur
Anomaly Detector in containers
Microsoft Seeing AI – talking Camera for the Blind
Azure Cognitive service – computer vision
AI demo – computer vision
AI demo – Language Understanding Intelligent Service (LUIS)
Guidelines for human ai interaction
Module 2 – Describe fundamental principles of machine learning on Azure (30-35%)
Azure Machine Learning – SKU
Create no-code predictive models with Azure Machine Learning
==> video on regression, classification…
Machine learning algorithms
Tutorial: Predict automobile price with the designer (preview) ==> You should do it !!
Module 3 – Describe features of computer vision workloads on Azure (15-20%)
Computer Vision documentation
Classify images with the Custom Vision service
Custom Vision documentation
Sample for object detection
Azure Face detection demo
What is the Azure Face service?
Reading text with the Computer Vision service
Module 4 – Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
Explore natural language processing
Text Analytics API documentation
Module 5 – Describe features of conversational AI workloads on Azure (15-20%)
Training on Microsoft Learn
QnA Maker portal
Enterprise productivity Chatbot
FAQ Chatbot with data champion model