MCE Multi-Agent AI Solutions Certification (AI-500) Boot Camp

Upcoming Sessions

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Date

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Oct 12–16, 2026

Sarasota, FL · Onsite

$3,495.00

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Nov 9–13, 2026

Sarasota, FL · Onsite

$3,495.00

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Dec 7–11, 2026

Sarasota, FL · Onsite

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Jan 18–22, 2027

Sarasota, FL · Onsite

$3,495.00

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Feb 8–12, 2027

Sarasota, FL · Onsite

$3,495.00

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Apr 12–16, 2027

Sarasota, FL · Onsite

$3,495.00

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May 10–14, 2027

Sarasota, FL · Onsite

$3,495.00

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Training a team? Get a customized Team Quote Volume pricing available for groups and corporate training.

Upcoming Sessions Multi-Agent AI Solutions

Oct 12–16, 2026
Nov 9–13, 2026
Dec 7–11, 2026
Jan 18–22, 2027
Feb 8–12, 2027
Apr 12–16, 2027
May 10–14, 2027

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Course Details

MCE Multi-Agent AI Solutions Certification (AI-500) Boot Camp

Duration

5 Days

Exams Covered

AI-500

Delivery

Classroom Live
Remote Live

Included

Vouchers + Retake + Official Labs

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Course Description

Description

Build the expertise to design, develop, deploy, and manage enterprise multi-agent AI solutions with this intensive, instructor-led AI-500 Multi-Agent AI Boot Camp. The program prepares experienced AI and technology professionals for Exam AI-500: Designing and Implementing Multi-Agent AI Solutions and the Microsoft Certified: Multi-Agent AI Solutions Expert credential.

Across five hands-on training days, you’ll learn how to transform complex business objectives into scalable agentic AI architectures. Training covers defining agent roles and responsibilities, establishing autonomy and permissions, coordinating AI agents and tools, designing agent memory and communication, and implementing monitoring and observability from the beginning of the development process.

You’ll then apply these concepts using Microsoft’s modern AI development ecosystem, including Microsoft Foundry, Microsoft Agent Framework, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG). The boot camp also focuses on the operational requirements of production-ready AI, including AI evaluation, tracing and observability, token and cost optimization, security, authentication, guardrails, governance, and deployment strategies.

By the end of the AI-500 training, you’ll have a practical understanding of how to architect and operationalize secure, scalable, and reliable multi-agent AI systems designed for real-world enterprise environments—not simply proof-of-concept AI applications.

Students may have the option to take the AI-500 certification exam on-site during the bootcamp.

EXAMS INCLUDED

AI-500: Multi-Agent AI Solutions

Prerequisites

Prerequisite: The Microsoft Certified: Azure AI Apps and Agents Developer Associate certification (earned by passing AI-103) is required to earn the Microsoft Certified: Multi-Agent AI Solutions Expert credential. Prior hands-on experience developing AI solutions, working with Microsoft Foundry, Python, Azure services, and agentic AI technologies is strongly recommended.

Our Facilities

CAREER CAMPS FACILITIES

CAMPUS – Career Camps built out a stand alone training center (not a hotel conference room) with spacious classrooms, new desk, Herman Miller Aeron chairs & comfortable common areas. Each student has a dedicated desk with two monitors. Each classroom has a maximum of two rows – so everyone is able to be engaged without the “back row” feeling.

CLASSROOM EQUIPMENT – Students work on a dedicated Dell Client Desktop with 32GB memory with 512GB SSD drives – All Labs are executed the extremely fast Microsoft Data Center Hosted Lab Environment.

CAMPUS INTERNET – The campus is connected with a 1Gbps (1,000 Mbps) Verizon Fios Business Connection which provides complete internet (including VPN) access for students.

COMMON AREA – Amenities including snacks, drinks (Coffee, 100% juices, sodas, etc) all complimentary.

LODGING – We use the Hyatt Place Lakewood Ranch. This “upgraded” hotel offers extremely comfortable beds, great breakfast and very fast internet access.

NEAR BY AMENITIES – Many shops, restaurants and grocery options are available within walking distance. Additionally – the hotel provided scheduled shuttle services. Restaurants like Bone Fish Grill, Ruby Tuesday’s, Five Guys, Chipotle, Quiznos, Chili’s and over 20 additional choices in the immediate area. All of these options are offered in a pedestrian walking village.

Why Choose Us

CAREER CAMPS DIFFERENCE

Career Camps provides an in-depth hands on learning environment. Our instructors teach using demonstrations and explain concepts beyond the scope of the courseware. The best instructors are contracted from all across the US. These professionals are real world consultants who actually implement these technologies. Career Camps knows our clients work in the “real world” and it only makes sense to have an instructor with the experience in the real world.

Facilities – Many of our competitors over-crowd classrooms by placing 2 to 3 students per desk and 20+ students per instructor. Often these companies “extend” the life of very old equipment with slow performance on the software used today. Our average class size is 8 students. Our facilities have the best equipment with the most comfortable, focused environment for learning.

Instructors – Our CEO, Chester Flake holds one of the rarest Microsoft Certifications – the Microsoft Certified Learning Consultant (MCLC) Certification. This certification reflects a commitment to make sure our instructors are also actively engaged in real world consulting projects. Students expect a professional who can answer questions and demonstrate the technology.

Face to Face Training – We believe the best way to interact and learn is face to face training. Many of our competitors which offer local training are simply providing students with headphones/mic to attend class with an instructor at a remote location.

Test Pass – We offer a free retake voucher (if needed) for each of the exams required for certification. Any training center offering a “100% pass guarantee” would have to use unethical practices or unlimited test vouchers (which is not likely or practical).

Distractions – Students often look for a “local” training center so they can be close to home and work. Boot camp requires a tremendous time commitment during the program. Long class hours combined with self study each evening. The goal of boot camp is to achieve certification in a fraction of the time. We strongly recommend students attend camp away from home and work in a focused, distraction free environment.

Boot Camp – Boot camp is an accelerated training focused on teaching technology and testing students on the official exams. Most training providers “added” boot camps to the existing standard training classes they offer. These training centers think a boot camp is just a regular class where you send the student home with a voucher on the last day. Career Camps administers exams throughout the camp. Equally important – not every trainer can teach a boot camp and not all courseware is designed for boot camp format. Our trainers know the boot camp format and our courseware is designed for accelerated learning.

Florida – Career Camps has one of the most scenic locations boasting some of the best weather in US. We believe students should have a comfortable and inviting atmosphere while attending these otherwise intense programs. We place our location, facilities and amenities up against that any competitor.

Microsoft Gold Learning Partner

Career Camps has developed a comprehensive training / delivery format which focuses on learning beyond the core content accessible to any Microsoft training provider. Our program incorporates interactive demonstrations with explanations which go beyond the content of the book. Additional content, videos, labs & demonstrations are provided to expand on advanced topics – providing additional insight and perspective.

Career Camps training is not the typical book & PowerPoint presentation found at any local training center.

As a Microsoft Certified Partner with Gold Learning Competency – we adhere to the strict guidelines, standards and requirements to use Microsoft’s exclusive curriculum. More over – our standards go beyond the “minimum requirements” set forth by Microsoft Learning.

We leverage our partnership benefits of courseware customization to build end to end technology training solutions. Students gain practical skills which can be implemented immediately.

At most training centers – learning starts on the first day of class and ends on the last day. Our boot camp training program is designed to offer resources before, during and after.

What You'll Learn

In this AI-500 Multi-Agent AI Solutions Expert Boot Camp, you’ll develop the skills to design, build, evaluate, secure, and deploy production-ready multi-agent AI solutions on Microsoft Azure. You’ll learn how to:

Architect Multi-Agent AI Solutions – Design scalable agentic AI architectures, workflows, agent roles, autonomy levels, memory, communication, and tool integration.
Build AI Agents in Azure – Develop and orchestrate multi-agent applications using Microsoft Foundry and the Microsoft Agent Framework.
Implement Agent Orchestration – Build sequential, parallel, peer-to-peer, and orchestrator-based workflows that enable multiple AI agents to collaborate effectively.
Work with MCP and Agent Integrations – Use Model Context Protocol (MCP) and agent-to-agent communication to connect AI agents with tools, applications, APIs, and external services.
Implement RAG and AI Knowledge Systems – Build Retrieval-Augmented Generation (RAG) solutions using embeddings, vector search, semantic search, and enterprise data.
Manage Agent Memory and Context – Design short-term and long-term memory, context management, state persistence, and secure information sharing between agents.
Evaluate AI Agent Performance – Test agent behavior, tool usage, memory, retrieval quality, workflows, and overall solution performance using systematic AI evaluation strategies.
Monitor and Optimize AI Solutions – Implement tracing, observability, telemetry, token management, cost controls, performance optimization, and continuous improvement.
Secure Multi-Agent AI Applications – Apply identity, authentication, authorization, Azure RBAC, secrets management, network security, and Zero Trust principles.
Implement AI Guardrails and Responsible AI – Protect AI applications with input, output, and tool-use guardrails while addressing responsible AI, governance, and security requirements.
Deploy AI Solutions to Production – Implement CI/CD, testing, release management, infrastructure as code, blue/green deployments, canary releases, and rollback strategies for multi-agent applications.
Prepare for the AI-500 Exam – Reinforce the skills and concepts covered by Exam AI-500: Designing and Implementing Multi-Agent AI Solutions and prepare for Microsoft’s Multi-Agent AI Solutions Expert certification.

Course Outline

Module 1: Architect Multi-Agent AI Solutions

Understand multi-agent AI architecture and production requirements
Decompose business goals into workflows, agents, subagents, and tools
Design sequential, parallel, peer-to-peer, and orchestrator-based workflows
Define agent personas, scopes, boundaries, autonomy levels, and behavioral guidelines
Establish tool permissions, authentication, and security boundaries
Design human-in-the-loop workflows and human-AI experiences
Design short-term and long-term agent memory
Implement context sharing across agents
Select appropriate AI models based on task requirements
Design agent-to-agent and agent-to-tool communication
Plan Zero Trust architecture for multi-agent AI systems
Design state persistence and tenant isolation
Select Azure compute resources based on scalability, reliability, security, and cost
Design observability, tracing, logging, and monitoring architectures
Establish development environments and SDLC practices for multi-agent AI

Module 2: Develop Multi-Agent AI Solutions in Azure

Prompt Engineering and Agent Behavior
Implement advanced prompt engineering techniques
Use examples and dynamic context injection
Create defensive prompts and behavioral guidelines
Manage the prompt lifecycle
Build context-aware agent behaviors
Develop model and agent fine-tuning strategies
Agent Memory, Context, and Knowledge
Design context management for individual and multi-agent systems
Implement context accumulation, retrieval, injection, and compaction
Design secure agent memory strategies
Manage session, shared, and long-term memory
Implement multi-agent Retrieval-Augmented Generation (RAG)
Improve chunking, embeddings, and retrieval precision
Integrate search and semantic search
Connect agents to knowledge sources through RAG and MCP
Tools and Integrations
Implement function calling and tool use
Integrate external resources and services
Design and build Model Context Protocol (MCP) servers and clients
Connect MCP solutions using Azure Functions, Azure Logic Apps, and Azure API Management
Implement tool validation and error handling
Create fallback strategies for failed tools and services
Multi-Agent Orchestration
Implement hub-and-spoke architectures
Implement sequential and parallel agent workflows
Implement peer-to-peer agent communication
Implement orchestrator-subagent patterns
Integrate human approval and override workflows
Implement prompt, semantic, and response caching
Manage agent spawning and concurrent execution
Integrate existing agents using MCP and Agent2Agent (A2A)
Build multi-agent solutions using Microsoft Agent Framework
Work with LangChain and LangGraph orchestration patterns
Implement middleware for logging, authorization, and exception handling
Explore advanced multi-agent capabilities using Hugging Face Transformers

Module 3: Evaluate, Optimize, and Monitor Multi-Agent AI Solutions

AI Evaluation and Validation
Design evaluation strategies for multi-agent applications
Evaluate agent memory and context
Evaluate knowledge retrieval and RAG performance
Evaluate tool usage and tool results
Evaluate prompt effectiveness
Implement human review processes using Microsoft Foundry
Performance and Quality Optimization
Optimize agent task duration and workflow parallelism
Manage rate limits and concurrent execution
Diagnose context-window problems
Address summary drift and loss of entity continuity
Improve vector-based recall and context retrieval
Implement continuous improvement strategies
Use LLM-as-a-judge evaluation
Generate synthetic evaluation data
Implement user feedback loops and semantic optimization
Observability and Monitoring
Monitor agent health and workflow reliability
Track workflow failures and agent coordination
Implement cross-service trace correlation
Detect behavioral drift and quality regression
Monitor Azure service availability and performance
Track SLA and reliability requirements
Implement token usage controls
Optimize tool calls and agent loops
Monitor AI costs, quotas, allocations, and chargebacks
Implement Microsoft Foundry tracing
Track prompts, tokens, correlation IDs, and execution activity
Configure alerts and automated remediation

Module 4: Secure and Govern Multi-Agent AI Solutions

Security and Identity
Implement identity-based access controls
Establish network boundaries and security policies
Configure Azure RBAC
Design authentication flows for multi-agent applications
Implement OAuth 2.0 and API-key authentication
Understand on-behalf-of authentication and user impersonation
Secure agent-to-agent and agent-to-tool communication
Implement Azure Key Vault for secrets and certificates
Manage secret rotation and encryption
Apply shift-left security principles
Use AI Red Teaming capabilities in Microsoft Foundry
AI Guardrails and Responsible AI
Design multi-layer guardrail strategies
Protect user inputs and agent outputs
Secure tool calls and tool responses
Create custom guardrails for business and domain requirements
Test and validate guardrails
Use synthetic data for guardrail testing
Apply responsible AI principles to multi-agent solutions

Module 5: Deploy Multi-Agent AI Solutions to Azure

Plan development, test, acceptance, and production environments
Design DTAP deployment strategies
Implement blue/green deployments
Implement canary releases
Create multi-environment release strategies
Develop rollback procedures
Implement unit testing
Implement integration and regression testing
Automate AI evaluations
Design CI/CD pipelines
Apply infrastructure-as-code deployment practices
Automate testing and release processes
Prepare multi-agent AI solutions for production
Exam Preparation and AI-500 Review
Review the official AI-500 exam objectives
Map hands-on skills to the four AI-500 exam domains
Practice multi-agent architecture scenarios
Review Microsoft Foundry and Agent Framework concepts
Review MCP, RAG, A2A, and orchestration patterns
Review security, governance, evaluation, and deployment scenarios
Identify common AI-500 exam knowledge gaps
Final exam readiness review

Frequently Asked Questions

What is the Microsoft AI-500 Multi-Agent AI Boot Camp?

The AI-500 Boot Camp is an intensive, instructor-led training program designed to prepare experienced AI professionals for Exam AI-500: Designing and Implementing Multi-Agent AI Solutions. The course focuses on designing, developing, deploying, securing, and optimizing production-ready multi-agent AI and agentic AI solutions using Microsoft's AI technologies.

Is AI-103 required before taking the AI-500 exam?

AI-103 is not required simply to sit for the AI-500 exam. However, to earn the Microsoft Certified: Multi-Agent AI Solutions Expert certification, you must hold the Microsoft Certified: Azure AI Apps and Agents Developer Associate certification, which is earned by passing Exam AI-103.

Who should take the AI-500 Multi-Agent AI Boot Camp?

The boot camp is designed for AI engineers, machine learning engineers, AI architects, software developers, cloud engineers, data scientists, and experienced AI professionals who are responsible for designing and implementing advanced agentic AI systems. It is particularly suited to professionals who already have experience developing AI applications and want to advance into multi-agent AI architecture and engineering.

What does the AI-500 exam cover?

AI-500 focuses on designing and implementing multi-agent AI solutions, including agent architecture, orchestration, communication, memory, tools, security, evaluation, observability, deployment, and optimization. Candidates need to understand how to move multi-agent systems from development and experimentation into reliable production environments.

What technologies are covered in the AI-500 Boot Camp?

The training covers Microsoft's modern agentic AI ecosystem, including Microsoft Foundry, Microsoft Agent Framework, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), Python, and agent orchestration technologies. Training also addresses the Azure services and infrastructure needed to deploy production-ready AI solutions.

Is the AI-500 Boot Camp hands-on?

Yes. The AI-500 Boot Camp emphasizes practical development and implementation of multi-agent AI solutions. Participants work with agent frameworks, orchestration, tools, retrieval, evaluation, observability, security, and deployment concepts designed to reflect real-world enterprise AI development.