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Optimize multi-agent performance and cost in Microsoft Foundry. Design model routing strategies across agent ecosystems, implement multi-level caching architectures, optimize token usage and context management across agent chains, and systematically analyze quality-cost-latency trade-offs.

Units in this learning path:

• Introduction
• Design Model Route Agent Ecosystems
• Implement Multi Level Cache Strategies
• Optimize Token Usage Context Management
• Balance Quality Cost Latency Tradeoffs
• Knowledge Check
• Summary

Products: Azure, Microsoft Foundry

Roles: AI Engineer, Solution Architect

Level: Advanced

Subjects: Artificial Intelligence, Machine Learning

Duration: 40 minutes

Optimize query and operation performance in Azure Cosmos DB for NoSQL

Modules in this learning path:

• Choose Indexes Azure Cosmos Db SQL API
• Measure Index Azure Cosmos Db SQL API
• Implement Integrated Cache

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 114 minutes

Learn how to optimize query performance and reduce costs for Azure Cosmos DB for NoSQL workloads by configuring indexes and selecting consistency levels.

Units in this learning path:

• Introduction
• Understand Indexes Cosmos Db
• Configure Range Composite Indexes
• Tune Vector Indexes Embeddings
• Reduce Ru Costs Strategic Indexing
• Choose Consistency Levels Performance
• Exercise Optimize Query Performance
• Knowledge Check
• Summary

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Databases, Artificial Intelligence

Duration: 96 minutes

Optimize query performance in Azure SQL

Modules in this learning path:

• Explore Query Performance Optimization
• Explore Performance Based Design
• Evaluate Performance Improvements

Products: Azure SQL Database, SQL Server

Roles: Data Analyst, Data Engineer, Database Administrator, Developer

Level: Intermediate

Subjects: Databases

Duration: 236 minutes

Optimize query performance in Azure DocumentDB by building effective indexing strategies. Create single-field, compound, multi-key, and specialized indexes. To maintain performance at scale, analyze query execution with the explain() command and monitor index health.

Units in this learning path:

• Introduction
• Understand How Indexes Work
• Create Single Field Compound Indexes
• Work Multi Key Specialized Index
• Analyze Query Performance Explain
• Monitor Optimize Indexes
• Exercise Build Indexing Strategy
• Knowledge Check
• Summary

Products: Azure Documentdb

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 83 minutes

Diagnose and fix semantic model and report performance issues. Use Performance analyzer to identify bottlenecks, optimize DAX calculations, reduce cardinality, and implement aggregations to improve query speed.

Units in this learning path:

• Introduction
• Performance Analyzer
• Optimize Dax
• Reduce Cardinality
• Implement Aggregations
• Troubleshoot
• Exercise
• Knowledge Check
• Summary

Products: Fabric, Power Bi

Roles: Data Analyst

Level: Advanced

Subjects: Data Analytics, Data Modeling

Duration: 78 minutes

Learn how to configure workforce management in Dynamics 365 Contact Center to forecast demand, plan shifts, schedule representatives, and integrate with third-party solutions.

Units in this learning path:

• Introduction
• Explore Workforce Management Capabilities
• Configure Forecasting
• Configure Shift Management Scheduling
• Integrate Third Party
• Knowledge Check
• Summary

Products: Dynamics Contact Center, Dynamics 365

Roles: Functional Consultant, Administrator

Level: Intermediate

Subjects: Customer Relationship Management

Duration: 42 minutes

Azure Database for PostgreSQL uses vacuum and autovacuum to remove rows that have been marked as soft-deleted after an update or deletion.

Units in this learning path:

• Introduction
• Explain Purpose Vacuum Autovacuum
• Configure Autovacuum Server Parameters
• Exercise Configure Autovacuum Server Parameters
• Knowledge Check
• Summary

Products: Azure Database Postgresql

Roles: Database Administrator

Level: Intermediate

Subjects: Databases

Duration: 24 minutes

Tune pgvector configuration, select vector indexes, design efficient data layouts, and scale Azure Database for PostgreSQL for high-performance AI workloads.

Units in this learning path:

• Introduction
• Tune Postgresql Pgvector
• Choose Configure Vector Indexes
• Optimize Data Layout
• Scale High Volume Workloads
• Connection Optimization
• Exercise Optimize Vector Search
• Knowledge Check
• Summary

Products: Azure Database Postgresql

Roles: Developer

Level: Intermediate

Subjects: Databases, Artificial Intelligence

Duration: 111 minutes

This module introduces ways to use the Xbox app and Windows gaming features to optimize your PC gaming experience across several types of features.

Units in this learning path:

• Introduction
• Xbox App Gaming Hub
• Exercise Consolidate Games
• Performance Gaming Features
• How to Use Exercise
• Knowledge Check
• Summary

Products: Windows 11

Roles: Business User, Student

Level: Beginner

Duration: 22 minutes

Learn how to optimize your business process with the process advisor capability in Microsoft Power Automate.

Units in this learning path:

• 1 Introduction
• 2 Get Familiar
• 3 Create Recording
• 4 Edit Recordings Group Actions
• 5 Analyze Recordings Interpret Results
• 6 Automation Recommendations
• 7 Check
• 8 Summary

Products: Power Platform, Power Automate

Roles: Maker, Business User

Level: Beginner

Subjects: Process Workflow

Duration: 26 minutes

Optimizing Costs for Microsoft Workloads on AWS teaches Developers, Solutions Architects, IT managers, and DevOps Engineers how to determine the right cost optimization techniques and tools to achieve lower costs and better performance for…