Microsoft Azure AI Fundamentals (AI-900) Certification Study Notes

Pass the AI Fundamentals certification

This repository is part of a course will give you everything you need to pass the Azure AI Fundamentals (AI-900) certification. This is the foundational certification for doing Machine Learning and Data Science using Azure and its specialized services. The course will go into every content that is relevant to pass the certification including how to create a study guide and strategy to pass the exam.

This course includes and covers all of my study notes so that you can use them in addition to your own notes.

1. Get Started with AI
2. Visual Tools for ML
3. Computer Vision
4. Natural Language Processing
5. Decision Support

This course contains a complete walkthrough over all of the content relevant for the AI-900 certification with a summary and specialized notes after each sections, following the same content that is available as Learning Paths. Aside from the video content, create your own study notes and strategy using the Study notes for the Azure AI Fundamentals Certification

🚀 Watch the Video course

💡 How can I pass the AI 900 Certification?

Start by creating your own study strategy. This repository has my own notes but you should create yours as part of studying for the course. I show you how I did it below 👇

Centralized details

• Download the skills outline

• Go through the 5 Learning Paths:

1. Get Started with AI
2. Explore Visual Tools for ML
3. Explore Computer Vision
4. Explore Natural Language Processing
5. Explore Decision Support

Next, go through each Learning Path and create a markdown file for each that includes every learn module.

• Summarize

Sample repo structure:

.
├── 1-get-started-with-ai.md
├── 2-visual-tools-for-ml.md
├── 3-computer-vision.md
├── 4-natural-language-processing.md
├── 5-decission-support.md
└── README.md

1. Create a repository and add the markdown files, one for each section
2. Start summarizing, adding the Learning Path and Learning Module for each section
3. Capture services, definitions, and any key differentiators

Sample section:

## Main topic

### Service Name

Definition: Some definition

Features:

* Feature 1
* Feature 2

Find key differences for similar services. For example, IoT Hub vs. IoT Central:

IoT Hub: More control, less managed (no dashboard). Telemetry analysis.

IoT Central: Less control, more managed (dashboard included). Telemetry analysis.

📚 Resources

If you are looking for more resources, here are some that I found helpful:

• Azure AI Fundamentals Certification
• Azure AI Fundamentals Certification Study Guide