AI-901: Microsoft Azure AI Fundamentals for Python Developers
Foundational, hands-on AI-901 prep. Learn Responsible AI, Foundry models, prompts, agents, text, speech, vision, and Content Understanding — all on Microsoft Foundry using Python.
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Exam Preparation Included
Practice with real exam-style questions for the AI-901 certification. AI-powered feedback helps you understand every answer.
About This Course
Get hands-on with Microsoft Azure AI and Microsoft Foundry to prepare for the AI-901 certification exam. This foundational, AI-led course walks you through the two exam objectives: identifying AI concepts and capabilities (responsible AI, model components, AI workloads) and implementing AI solutions using Microsoft Foundry (generative AI apps & agents, text & speech, computer vision & image generation, and information extraction with Azure Content Understanding). Every topic is paired with a guided hands-on lab in the browser-based Python + AI VS Code environment. You will build chat clients, agents, text analysis apps, speech-enabled applications, vision/image-gen experiences, and a Content Understanding document pipeline all against a real Azure subscription before finishing with a capstone multimodal Foundry assistant.
Course Curriculum
22 Lessons
Responsible AI Principles
Learn Microsoft's six principles of Responsible AI — fairness, reliability & safety, privacy & security, inclusiveness, transparency, and accountability — and how Azure AI Content Safety enforces them inside Microsoft Foundry. Taught by Skill Me UP Steve.
Responsible AI Principles — Lab Exercises
Hands-on with Azure AI Content Safety in Microsoft Foundry — run harm-category evaluations, jailbreak/prompt-shield detection, and map results to the six Responsible AI principles.
AI Models & Configurations
Understand how generative AI models work under the hood, how to pick a model in the Foundry catalog, and how to tune deployment configuration parameters (temperature, top_p, max tokens, system prompt, etc.).
AI Models & Configurations — Lab Exercises
Browse the Foundry model catalog, create a Foundry project, deploy a chat model, and test it from the playground and the Foundry SDK — tuning temperature, top_p, and max tokens to see how outputs change.
AI Workloads Overview
Tour the five AI workload families on Azure — generative & agentic AI, text analysis, speech, computer vision, and information extraction — and learn how to pick the right Azure service for a real-world scenario.
AI Workloads Overview — Lab Exercises
Scenario-matching workshop — read real business descriptions, identify the right AI workload family, pick the Azure service, and validate your choice by calling that service from Python.
Prompt Engineering & Portal Chat
Craft effective system and user prompts for generative AI models, then deploy a model and interact with it in the Foundry portal playground.
Prompt Engineering & Portal Chat — Lab Exercises
Use the Foundry playground to iterate on system prompts, tune parameters, and test prompt-engineering patterns (role, few-shot, chain-of-thought, JSON-only output) against a deployed chat model.
Foundry SDK — Building a Chat Client
Move from portal to code — build a lightweight Python chat client against your Foundry deployment using the azure-ai-inference SDK and DefaultAzureCredential, then add streaming and message history.
Foundry SDK — Building a Chat Client — Lab Exercises
Take the ai-901-chat-client starter project and turn it into a full REPL chat app — add a system prompt, streaming responses, a conversation history buffer, and keyless auth with DefaultAzureCredential.
Single-Agent Solutions in Foundry
Learn how Foundry agents differ from raw chat completions — agents, threads, runs, tools — and design a single-agent solution that uses a custom Python function tool.
Single-Agent Solutions in Foundry — Lab Exercises
Build a single-agent solution in the Foundry portal, then connect a lightweight Python client to it — adding a custom function tool, sending messages, and interpreting the run results.
Text Analysis with Foundry
Learn the common text analysis techniques tested on the AI-901 — keyword extraction, entity recognition, sentiment analysis, and summarization — and see how Azure AI Language and Foundry-hosted LLMs compare for each.
Text Analysis with Foundry — Lab Exercises
Build a lightweight text analysis application against a small corpus of product reviews using the azure-ai-textanalytics SDK — extract key phrases, recognize named entities, score sentiment, and summarize.
Speech AI with Foundry Tools
Cover the features of speech recognition and speech synthesis, the difference between Azure Speech and multimodal chat models that accept audio, and when to use each.
Speech AI with Foundry Tools — Lab Exercises
Build a speech-enabled app — transcribe audio with Azure Speech, synthesize voice responses, and then wire a spoken prompt straight into a multimodal model via Foundry.
Computer Vision & Image Generation
Learn the core computer-vision capabilities on Azure — image analysis, OCR, object detection, multimodal vision-in-chat — plus image generation models available through Foundry.
Computer Vision & Image Generation — Lab Exercises
Interpret retail-shelf images with a multimodal model, call azure-ai-vision for structured analysis, and generate new marketing imagery with a Foundry image-generation model.
Information Extraction with Content Understanding
Extract structured information from documents, images, audio, and video using Azure Content Understanding in Microsoft Foundry Tools — analyzers, schemas, and output shapes.
Information Extraction with Content Understanding — Lab Exercises
Build a lightweight information-extraction pipeline — define a Content Understanding analyzer, run it against a sample invoice, a retail image, and an audio clip, and return structured JSON.
Capstone Briefing
Brief overview of the Northwind Horizon capstone scenario, the multimodal Foundry assistant students will build, and how each capability maps back to the AI-901 exam objectives.
Capstone Briefing — Lab Exercises
Capstone — wire a FastAPI multimodal assistant for Northwind Horizon that combines Foundry chat, Azure Speech, vision-in-chat, and Content Understanding into one coherent app.
This course includes:
- 24/7 AI Instructor Support
- Live Lab Environments
- 11 Hands-on Lessons
- Exam Prep Included
- Completion Badge
Earn Your Badge
Complete all lessons to unlock the AI-901: Azure AI Fundamentals — Python Developers achievement badge.
AI-901: Azure AI Fundamentals — Python Developers
Awarded for completing AI-901: Microsoft Azure AI Fundamentals for Python Developers. Demonstrates hands-on proficiency with Microsoft Foundry using Python — Responsible AI, model selection, prompts, agents, text, speech, vision, and Content Understanding.
Skills You'll Earn
Complete all lessons in this course to earn this badge