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Design a machine learning solution with Azure Machine Learning v2

Modules in this learning path:

• Design Data Ingestion Strategy for Machine Learning Projects
• Design Machine Learning Model Training Solution
• Design Model Deployment Solution
• Design Machine Learning Operations Solution

Products: AI Services, Azure Databricks, Azure Devops, Azure Machine Learning, Azure Synapse Analytics, Github

Roles: Data Scientist

Level: Beginner

Subjects: Machine Learning

Duration: 162 minutes

Design a model deployment solution with Azure Machine Learning Python SDK v2

Units in this learning path:

• Introduction
• Understand How Model Consumed
• Decide Real Time Batch Deployment
• Knowledge Check
• Summary

Products: Azure Machine Learning

Roles: Data Scientist

Level: Beginner

Subjects: Artificial Intelligence, Machine Learning

Duration: 27 minutes

Evaluate how Microsoft Designer and Copilot support creative planning, storyboarding, and script writing tasks for music video preproduction.

Units in this learning path:

• Introduction
• Production
• Use Microsoft Designer Copilot Storyboard
• Leverage Copilot
• Knowledge Check
• Exercise
• Summary

Products: Ms Copilot

Roles: Student, Maker, K 12 Educator

Level: Beginner

Subjects: Artificial Intelligence

Duration: 62 minutes

Detect objects in images

Units in this learning path:

• Introduction
• Understand Object Detection
• Train Object Detector
• Use Trained Detector
• Exercise Custom Vision
• Knowledge Check
• Summary

Products: AI Services, Azure Custom Vision

Roles: AI Engineer, Developer

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 65 minutes

Learn the basics of AI Builder Object detection and how it can benefit your organization.

Units in this learning path:

• 1 Introduction
• 2 Create Model
• 3 Use Model
• 4 Check
• 5 Summary

Products: AI Builder, Power Platform, Power Automate

Roles: Business User, Maker

Level: Beginner

Subjects: Artificial Intelligence, Business Applications

Duration: 25 minutes

Detect, analyze, and recognize faces

Units in this learning path:

• Introduction
• Understand Capabilities of Face Service
• Detect Analyze Faces
• Compare Match Detected Faces
• Understand Considerations for Face Analysis
• Exercise Identify Faces
• Knowledge Check
• Summary

Products: Azure Computer Vision, Azure Face, Azure AI Foundry

Roles: AI Engineer, Developer

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 54 minutes

Learn how to develop AI agents on Azure using the Microsoft Foundry Agent Service and Microsoft Agent Framework. AI-3026

Modules in this learning path:

• Develop AI Agents Azure Vs Code
• Build Agent with Custom Tools
• Connect Agent to Mcp Tools
• Introduction Foundry Iq
• Integrate Foundry Agent with M365
• Build Agent Workflows Microsoft Foundry
• Develop AI Agent with Semantic Kernel
• Orchestrate Sk Multi Agent Solution
• Discover Agents with A2a

Products: AI Services, Microsoft Foundry

Roles: AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, Machine Learning, Natural Language Processing

Duration: 593 minutes

Learn how to build, test, and deploy AI agents using Microsoft Foundry Agent Service through both the Azure portal and Visual Studio Code extension.

Units in this learning path:

• Introduction
• Understand AI Agents Foundry
• Explore Development Approaches
• Build Agent Azure Portal
• Set Up Vs Code
• Configure Manage Agents
• Extend Agent Capabilities
• Test Deploy Integrate
• Exercise
• Knowledge Check
• Summary

Products: Azure AI Foundry, Azure AI Foundry Agent Service, Azure AI Foundry Sdk

Roles: AI Engineer, Developer, Data Scientist, Solution Architect

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 96 minutes

Learn how to build, test, and deploy AI agents using the Microsoft Foundry extension in Visual Studio Code.

Units in this learning path:

• Introduction
• Get Started with Extension
• Agent Development
• Extend Agent Capabilities
• Exercise
• Knowledge Check
• Summary

Products: Azure AI Foundry, Azure AI Foundry Agent Service

Roles: AI Engineer, Data Scientist

Level: Beginner

Subjects: Artificial Intelligence

Duration: 48 minutes

Use Azure AI to extract information from content. (AI-3002)

Modules in this learning path:

• Analyze Content AI
• Analyze Content AI API
• Use Prebuilt Form Recognizer Models
• Work with Form Recognizer
• AI Knowledge Mining

Products: AI Services, Microsoft Foundry, Azure Cognitive Search

Roles: AI Engineer, Developer

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 258 minutes

Retrieval Augmented Generation (RAG) is a common pattern used in generative AI solutions to *ground* prompts with your data. Microsoft Foundry provides support for adding data, creating indexes, and integrating them with generative AI models to help you build RAG-based solutions.

Units in this learning path:

• Introduction
• Ground Language Model
• Search Data
• Openai Client
• Build Copilot
• Exercise
• Knowledge Check
• Summary

Products: Azure AI Foundry, Azure Cognitive Search

Roles: Data Scientist, AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, Machine Learning, Natural Language Processing

Duration: 78 minutes

Break down complex tasks with intelligent collaboration. Learn how to design multi-agent solutions using connected agents.

Units in this learning path:

• Introduction
• Understand Connected Agents
• Design Multi Agent Solution
• Exercise
• Knowledge Check
• Summary

Products: Azure AI Foundry, Azure AI Foundry Agent Service, Azure AI Foundry Sdk

Roles: AI Engineer, Developer, Solution Architect, Student

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 46 minutes