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Explore the power of AI tools in education and training plans. Learn how to integrate AI tools to enhance creativity, productivity, and efficiency in your training sessions. Understand the potential and limitations of AI through real-life examples and enhance your training experience.

Units in this learning path:

• Introduction
• Elevating Training Sessions with AI Tools
• Explore the Potential and Limitations of AI Tools
• Knowledge Check
• Summary

Products: Foundry Tools, Azure Machine Learning, Azure Machine Learning Designer, M365 Apps, Azure Translator Text, Azure Translator Speech, Ms Copilot, Language Service

Roles: K 12 Educator, Business User, Higher Ed Educator, Data Engineer, School Leader

Level: Beginner

Subjects: Artificial Intelligence

Duration: 17 minutes

Implement enterprise CI/CD pipelines for multi-agent systems using GitHub Actions and Microsoft Foundry. Design coordinated deployment pipelines with agent version compatibility validation, implement canary and blue-green deployment strategies, configure multi-environment strategies, and automate rollback triggered by quality regression metrics.

Units in this learning path:

• Introduction
• Design Multi Agent Deployment Pipelines
• Implement Progressive Deployment Strategies
• Configure Multi Environment Agent Strategies
• Automate Rollback Procedures
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry, Github

Roles: AI Engineer, Devops Engineer, Solution Architect

Level: Advanced

Subjects: Artificial Intelligence, Devops

Duration: 41 minutes

Generative Artificial Intelligence (AI) engineering with Azure Databricks uses the platform's capabilities to explore, fine-tune, evaluate, and integrate advanced language models. By using Apache Spark's scalability and Azure Databricks' collaborative environment, you can design complex AI systems.

Modules in this learning path:

• Introduction Language Models Databricks
• Retrieval Augmented Generation Azure Databricks
• Multistage Reasoning Azure Databricks
• Fine Tune Azure Databricks
• Evaluate Language Models Azure Databricks
• Responsible Language Models Azure Databricks
• Implement Llmops Azure Databricks

Products: Azure Databricks

Roles: Data Scientist, AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, Machine Learning

Duration: 417 minutes

Explore the data science process and learn how to train machine learning models to accomplish artificial intelligence in Microsoft Fabric. (DP-604T00)

Modules in this learning path:

• Introduction End Analytics Use Microsoft Fabric
• Get Started Data Science Fabric
• Explore Data for Data Science Microsoft Fabric
• Preprocess Data with Data Wrangler Microsoft Fabric
• Train Track Model Fabric
• Generate Batch Predictions Fabric

Products: Fabric

Roles: Data Scientist, Data Analyst, Data Engineer

Level: Beginner

Subjects: Machine Learning, Data Analytics, Data Engineering, Data Integration, Data Management

Duration: 329 minutes

A practical approach to implementing generative AI responsibly, and exploring guardrails in AI Foundry portal.

Units in this learning path:

• Introduction
• Plan Responsible AI
• Identify Harms
• Measure Harms
• Mitigate Harms
• Operate Responsibly
• Exercise Content Filters
• Knowledge Check
• Summary

Products: Microsoft Foundry

Roles: AI Engineer, Developer, Solution Architect, Student

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 45 minutes

Implement advanced retrieval-augmented generation (RAG) pipelines for production AI agents using Azure AI Search and Microsoft Foundry. Design hybrid search architectures, implement reranking strategies, configure dynamic knowledge source routing, and optimize chunking and embedding strategies.

Units in this learning path:

• Introduction
• Design Hybrid Search Architectures
• Implement Rerank Context Rank
• Design Dynamic Knowledge Source Route
• Optimize Chunk Embed Strategies
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry, Azure Cognitive Search

Roles: AI Engineer, Solution Architect, Data Scientist

Level: Advanced

Subjects: Artificial Intelligence, Machine Learning

Duration: 41 minutes

Implement advanced multi-agent orchestration patterns in Microsoft Foundry. Design hub-and-spoke coordination with central orchestrator agents, implement parallel agent spawning with synchronization, configure supervisor patterns for hierarchical task delegation, and evaluate orchestration framework trade-offs.

Units in this learning path:

• Introduction
• Differentiate Agentic Multi Agent Architectures
• Examine Advanced Orchestration Architectures
• Implement Hub Spoke Orchestration
• Design Parallel Agent Spawn Synchronization
• Compare Orchestration Frameworks
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry, Foundry Agent Service

Roles: AI Engineer, Solution Architect

Level: Advanced

Subjects: Artificial Intelligence

Duration: 48 minutes

Learn how to implement best practices for AI agent workloads by leveraging frameworks like AI Center of Excellence, FinOps, GenAI Ops, Cloud Adoption Framework, and Well-Architected Framework.

Units in this learning path:

• AI Center Excellence
• Finops Framework
• Genai Ops
• Cloud Adoption Framework
• Well Architected Framework
• Knowledge Check
• Summary

Products: Microsoft Foundry, Foundry Tools, Azure Openai, Ms Copilot

Roles: Developer

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 34 minutes

Implement distributed observability infrastructure for production multi-agent AI solutions using OpenTelemetry and Azure Monitor. Design distributed tracing architectures with correlation propagation, implement structured logging for agent decision paths, configure telemetry aggregation, and build anomaly detection for agent behavior patterns.

Units in this learning path:

• Introduction
• Design Distributed Trace Multi Agent Systems
• Implement Structured Log Agent Decisions
• Configure Telemetry Aggregation Dashboards
• Build Anomaly Detection Agent Behavior
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry, Azure Monitor

Roles: AI Engineer, Devops Engineer, Solution Architect

Level: Advanced

Subjects: Artificial Intelligence, Devops

Duration: 41 minutes

Do you want to bring AI to your business to improve your business performance? AI Builder offers a wide array of AI capabilities, such as text recognition and object detection. This learning path guides you through each use case, the creation of the models, and how to use them.

Modules in this learning path:

• Get Started with Form Processing
• Get Started with AI Builder Text Recognition
• Get Started with AI Builder Sentiment Analysis
• Get Started with AI Business Card Reader
• Get Started with AI Builder Object Detection
• Get Started with AI Builder Language Detection
• Get Started with AI Builder Key Phrase Extraction
• AI Builder Power Automate
• AI Builder Receipt Processing

Products: AI Builder

Roles: Maker, Business User

Level: Beginner

Subjects: Artificial Intelligence

Duration: 265 minutes

Enable dynamic tool access for your Azure AI agents. Learn how to connect MCP-hosted tools and integrate them seamlessly into agent workflows.

Units in this learning path:

• Introduction
• Understand Mcp Tool Discovery
• Mcp Client Server Setup
• Use Azure AI Agents with Mcp
• Exercise
• Knowledge Check
• Summary

Products: Microsoft Foundry, Foundry Agent Service

Roles: AI Engineer, Developer, Solution Architect, Student

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 51 minutes

Learn to integrate Copilot Studio agents with enterprise systems. This learning path covers evaluating integration patterns, configuring connectors and REST API tools, grounding agents with enterprise knowledge sources, and connecting agents to external systems via MCP.

Modules in this learning path:

• Design Integration Strategies Agents Copilot Studio
• Take Action External Systems Connector Rest API Tools Copilot Studio
• Ground Agents Enterprise Knowledge Connectors Azure AI Search Copilot Studio
• Integrate Agents External Systems Mcp Copilot Studio

Products: Microsoft Copilot Studio

Roles: Maker

Level: Intermediate

Subjects: Artificial Intelligence, Automation, Chatbots

Duration: 198 minutes