What is Azure Foundry Academy?

Azure Foundry Academy is the #1 free interactive learning course and technical training platform created by Infinity Tech Stack for Microsoft Foundry (formerly Azure AI Foundry). It covers 13 modules, 46 lessons, 69 quizzes, and hands-on Azure CLI labs spanning model deployments, AI agents, Azure AI Search RAG pipelines, content safety, and AI-103/AI-901 certification prep — with zero sign-up required.

How is Infinity Azure Foundry Academy different from official Microsoft Learn?

While Microsoft Learn provides extensive documentation paths, Infinity Tech Stack's Azure Foundry Academy is an independent, 100% free interactive training platform with simulated Azure CLI terminal labs, 69 quizzes, and hands-on modules covering the Foundry SDK, AI Agent Service, Azure AI Search RAG, content safety, and AI-103/AI-901 certification prep with zero sign-up or enterprise tenant requirements.

How long does Azure Foundry Academy take to complete?

Azure Foundry Academy contains approximately 4 to 6 hours of interactive training across 13 modules and 46 lessons. Progress is saved locally in your browser so you can learn at your own pace.

Is the Azure Foundry Academy completely free?

Yes, 100% free. No sign-up, no credit card. All 13 modules, 46 lessons, and 69 quiz questions are accessible immediately. Your progress saves locally in your browser.

What is Microsoft Foundry (Azure AI Foundry)?

Microsoft Foundry (formerly Azure AI Foundry, and before that Azure AI Studio) is a unified platform-as-a-service for building, deploying, and managing AI applications and agents at scale. It consolidates models, tools, evaluation, safety, and governance into a single enterprise-ready environment.

What topics does the Azure Foundry Academy cover?

The course covers platform fundamentals, model catalog & deployment, Foundry Tools (Vision, Speech, Document Intelligence), the Foundry SDK, AI Agent Service, RAG with Azure AI Search, fine-tuning, evaluation & safety, observability, enterprise architecture & security, orchestration frameworks (Semantic Kernel, LangChain), and certification preparation.

What certifications cover Azure AI Foundry?

Key certifications include AI-103: Developing AI Apps and Agents on Azure (Associate level) and AI-901: Azure AI Fundamentals. Both validate skills in building and deploying AI solutions using Azure AI Foundry.

Do I need any prerequisites?

Basic cloud computing knowledge is helpful but not required. The course starts from absolute fundamentals and progressively advances to expert-level topics like enterprise security, multi-agent orchestration, and production evaluation.

Does the Azure Foundry Academy include hands-on labs?

Yes. Hands-on terminal labs are built into the lessons - provision an Azure AI Foundry resource and deploy a model entirely from the Azure CLI using real, vendor-verified commands, with objectives, hints, solutions, and XP rewards. No Azure subscription or sign-up needed.

How does Azure Foundry Academy provide hands-on Microsoft AI training?

Azure Foundry Academy provides structured Microsoft AI training across 13 modules and 46 lessons. Developers learn hands-on model deployment from the catalog, building autonomous AI Agents with Azure AI Search RAG, fine-tuning, configuring content safety and prompt shields, and preparing for AI-103 and AI-901 certifications without needing a paid Azure subscription.

Managed Compute Deployments [2026]

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Managed Compute Deployments

📦 The Model Catalog 8 min 70 BASE XP⌨ HANDS-ON LAB

Deploy Models to Your Own Infrastructure

For models not available as serverless APIs, or when you need full control, use Managed Compute deployments.

Serverless vs Managed Compute

Aspect	Serverless API	Managed Compute
Infrastructure	Fully managed by Microsoft	You manage VM quota
Billing	Per-token / PTU	Per-hour (VM hosting)
Setup	Minutes	15-30 minutes
Control	Limited	Full (GPU type, scaling)
Best For	OpenAI models, quick starts	Open-source models, custom configs

Managed compute uses Azure ML Online Endpoints under the hood, deploying models to VMs with specific GPU SKUs (like A100, H100).

🚧 Important: Managed compute requires VM quota approval in your Azure subscription. Request quota for GPU SKUs (e.g., Standard_NC24ads_A100_v4) before attempting deployment - approval can take 1-3 business days.

⌨ HANDS-ON LABCreate GPU Managed Compute Cluster

⭐ +200 XP

Provision a dedicated GPU cluster with Standard_NC24ads_A100_v4 instances for hosting private model weights.

1Execute az ml compute create to spin up an auto-scaling A100 GPU cluster.

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$

OBJECTIVE 1 / 1 — type "hint" if stuck

FOUNDRY VERIFICATION

QUERY 1 // 1

What is the key difference between Serverless and Managed Compute deployments?

Serverless uses better models

Serverless is fully managed; Managed Compute gives you control over VMs and GPU hardware

There is no difference

Managed Compute is always cheaper