Microsoft Foundry Fundamentals: A Beginner’s Guide to Models, Workflows, and Possibilities by Microsoft Press
4h 6mIntermediate2026-07-14
Authors
Microsoft Press
Microsoft
Course details
As AI continues to reshape industries, mastering platforms like Azure Foundry is crucial for anyone looking to harness the power of large language models (LLMs) and machine learning (ML). This course offers a comprehensive but approachable pathway to begin to understand and work with AI models within the Azure ecosystem. Explore foundational concepts like model deployment, prompt engineering, monitoring, and governance, all delivered in an easy-to-follow video format. Gain a clear understanding of how to get started with Azure Foundry for your own projects.
Learn model deployment basics and about lifecycle management of AI models on the scalable infrastructure of Azure. Develop proficiency in evaluating and validating AI model outputs within a cloud-based environment. Cultivate expertise in implementing ethical AI governance and compliance standards using Foundry feature. Whether you’re a developer, a data scientist, or a tech enthusiast, this course can help you to unlock AI’s potential within the Azure platform.
Learning objectives
Set up your Azure environment and access Foundry tools and resources.
Deploy AI models and manage their lifecycle within the platform.
Configure and use agents to automate AI workflows.
Interact with and test AI models to validate outputs.
Implement responsible AI practices and governance measures.
Skills covered
Learn model deployment basics and about lifecycle management of AI models on the scalable infrastructure of Azure. Develop proficiency in evaluating and validating AI model outputs within a cloud-based environment. Cultivate expertise in implementing ethical AI governance and compliance standards using Foundry feature. Whether you’re a developer, a data scientist, or a tech enthusiast, this course can help you to unlock AI’s potential within the Azure platform.
Learning objectives
Set up your Azure environment and access Foundry tools and resources.
Deploy AI models and manage their lifecycle within the platform.
Configure and use agents to automate AI workflows.
Interact with and test AI models to validate outputs.
Implement responsible AI practices and governance measures.
Skills covered
Concepts
Introduction
- Microsoft Foundry Fundamentals - Introduction
Introduction to Microsoft Foundry
- Learning objectives
- What is Microsoft Foundry
- Why Foundry matters - AI in the enterprise
- Prerequisites and setting up your Azure environment
- Overview of Foundry interface and navigation
Exploring the Model Catalog
- Learning objectives
- Understanding model types and capabilities
- Browsing and selecting models
- Deploying your first model
- Hands-on - Simple deployment walkthrough
Interacting with Models
- Learning objectives
- Using the Playground for prompt testing
- Chat experience and output validation
- Understanding cost implications
- Hands-on - Testing prompts and reviewing outputs
- Connecting endpoints overview
Agents, Templates, and Fine-Tuning
- Learning objectives
- Understanding agents - what they are and why they re useful
- Exploring templates for quick solutions
- Introduction to fine-tuning concepts
- Hands-on - Configuring a simple agent
- Content understanding basics
Monitoring, Tracing, and Governance
- Learning objectives
- Tracing and monitoring model performance
- Evaluations and Metrics overview
- Implementing guardrails and risk alerts
- Governance and responsible AI in Foundry
- Hands-on - Setting up basic governance rules
Azure OpenAI Features and Management
- Learning objectives
- Stored completions and batch jobs
- Understanding My Assets - Models and endpoints
- Management Center overview
- Hands-on - Reviewing assets and endpoints
Summary
- Microsoft Foundry fundamentals - Summary