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Learn the concepts of agentic DevOps. Next, learn how to use GitHub Copilot, Azure DevOps MCP Server, and Azure SRE Agent to accelerate delivery, automate operations, and improve reliability across your DevOps workflows.

Modules in this learning path:

• Introduction Agentic Devops Microsoft Tools Azure
• Manage Azure Boards Using Github Copilot
• Manage Ado Mcp Server
• Optimize Azure Reliability Using Sre Agent
• Use Plan Mode Cloud Ops
• Use Github Copilot Cloud Operations
• Transition Traditional Ops Agent Automation

Products: Azure, Azure Devops, Azure Boards, Github

Roles: Administrator, Developer, Devops Engineer

Level: Intermediate

Subjects: Devops

Duration: 671 minutes

Performance optimization, also known as performance tuning, involves making changes to the current state of the semantic model so that it runs more efficiently. Essentially, when your semantic model is optimized, it performs better.

Units in this learning path:

• 1 Introduction
• 1a Optimization Techniques
• 2 Performance
• 3 Variables
• 4 Reduce Cardinality
• 5 Directquery Models
• 6 Aggregations
• 7 Check
• 8 Summary

Products: Power Bi, Power Platform

Roles: Data Analyst

Level: Intermediate

Subjects: Data Modeling

Duration: 69 minutes

This module explores comprehensive best practices for Microsoft 365 Copilot and key extension methods, ensuring you harness the full potential and versatility of Copilot's functionality.

Units in this learning path:

• Introduction
• Examine Working with AI
• Best Practices Copilot
• Examine Effective Prompt
• Review Prompting Best Practices
• Extend Copilot with Plugins
• Knowledge Check
• Summary

Products: M365, Office 365, Ms Copilot, M365 Apps

Roles: Administrator, Business Owner, Business User

Level: Beginner

Duration: 30 minutes

Learn how to select fine-tuning methods (SFT, RFT, DPO), recognize agent quality problems, prepare training data, and design optimization strategies using hyperparameter configuration and iterative evaluation.

Units in this learning path:

• Introduction
• Select Finetune Method
• Scenarios
• Prepare Data
• Optimize Finetune
• Exercise
• Knowledge Check
• Summary

Products: Microsoft Foundry

Roles: Data Scientist, AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, Machine Learning, Natural Language Processing

Duration: 89 minutes

Learn how you can evaluate and improve app load times. By regularly reviewing and measuring your app, you can proactively identify and remediate startup performance problems.

Units in this learning path:

• 1 Introduction
• 2 Monitor Start Performance Issues
• 3 Optimize on Start
• 4 Data Load Strategies
• 5 Check
• 6 Summary

Products: Power Apps

Roles: Maker

Level: Intermediate

Subjects: Custom App Development

Duration: 30 minutes

Learn how to optimize business processes using Microsoft 365 Copilot.

Modules in this learning path:

• Unlock Productivity Unleash Creativity AI Powered Chat
• Draft Impactful Documents Using AI
• Present Copilot Microsoft Powerpoint
• From Inbox Impact Improve Your Email Workflows AI
• Uncover New Data Insights AI

Products: M365, Office 365

Roles: Business User

Level: Beginner

Subjects: Artificial Intelligence, Business Applications, Compliance, Productivity, Security

Duration: 193 minutes

Microsoft Azure offers Azure Hybrid Benefit, which helps organizations reduce costs when migrating to the cloud environment. You can leverage several Azure discounts and combine them with other services and strategic pricing offerings.

Units in this learning path:

• Introduction
• Azure Hybrid Benefit Overview
• Azure Hybrid Benefit Capabilities
• Azure Hybrid Benefit Activation
• Optimize Usage Azure Hybrid Benefit
• Maximize Savings Azure Hybrid Benefit
• Knowledge Check
• Summary

Products: Azure, Azure Openai

Roles: Solution Architect, Technology Manager, AI Engineer

Level: Intermediate

Duration: 72 minutes

This module looks at cost models and cost optimization features in Azure NetApp Files.

Units in this learning path:

• Introduction
• Storage Cool Access
• Reserved Capacity
• Knowledge Check
• Summary

Products: Azure Netapp Files

Roles: Administrator, Solution Architect

Level: Intermediate

Subjects: Cloud Computing, Storage

Duration: 23 minutes

Optimize Azure SQL Database performance by choosing the right service tier and managing concurrency with isolation levels. Analyze queries with execution plans and DMVs. Use Query Store for plan management and resolve blocking and deadlocks.

Units in this learning path:

• Introduction
• Recommend Database Configurations
• Preserve Data Integrity Isolation Levels
• Evaluate Query Performance
• Monitor Tune Queries Query Store
• Identify Resolve Blocking Deadlocks
• Exercise Optimize Query Performance
• Knowledge Check
• Summary

Products: Azure, Azure SQL Database, SQL Server

Roles: Database Administrator, Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Cloud Computing

Duration: 104 minutes

Use AI and Copilot tools across Microsoft Intune and Microsoft Defender to prioritize endpoint issues, investigate threats, and apply targeted remediation actions.

Units in this learning path:

• Introduction
• Role of AI
• Copilot Security Threats
• AI Recommendations Intune
• Defender Insights Endpoint
• Knowledge Check
• Summary

Products: M365, Intune, Microsoft Defender

Roles: Administrator, Security Engineer

Level: Intermediate

Duration: 49 minutes

Explore complementary strategies to optimize generative AI model performance, including prompt engineering, system messages, model parameters, Retrieval Augmented Generation (RAG), and fine-tuning. Learn when to use each strategy and how to combine them.

Units in this learning path:

• Introduction
• Prompt Engineering
• Retrieval Augmented Generation
• Fine Tune Model
• Compare Combine Strategies
• Exercise
• Knowledge Check
• Summary

Products: Microsoft Foundry

Roles: Data Scientist, AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, Machine Learning, Natural Language Processing

Duration: 131 minutes

Learn how to optimize model training in Azure Machine Learning by using scripts, jobs, components and pipelines.

Modules in this learning path:

• Run Training Script Command Job Azure Machine Learning
• Train Models Training Mlflow Jobs
• Perform Hyperparameter Tuning Azure Machine Learning Pipelines
• Run Pipelines Azure Machine Learning

Products: Azure Machine Learning

Roles: Data Scientist

Level: Beginner

Subjects: Machine Learning

Duration: 157 minutes