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Microsoft Certified: Agentic AI Business Solutions Architect
Microsoft / Agentic-AIBuild the skills for your next mission.
This advanced certification validates an individual's expertise in designing, implementing, and managing sophisticated agentic AI solutions tailored for complex business environments.
Course objectives
Build practical skills across the key domains covered in Microsoft Certified: Agentic AI Business Solutions Architect (Agentic-AI).
Design Agentic AI SolutionsGather and analyze business requirements for agentic AI solutions, identifying key performance indicators and success metrics.
- Gather and analyze business requirements for agentic AI solutions, identifying key performance indicators and success metrics.
- Evaluate the suitability of agentic AI for specific business problems, differentiating from traditional AI/ML approaches.
- Architect multi-agent systems, defining agent roles, communication protocols, and collaboration strategies.
- Design for scalability, reliability, and fault tolerance in agentic AI architectures.
- Incorporate ethical AI principles, fairness, transparency, and accountability into agentic solution designs.
- Select appropriate agent frameworks and platforms (e.g., Microsoft Semantic Kernel, OpenAI Assistants API) based on solution requirements.
Implement Agentic AI ComponentsDevelop and configure agent personas, goals, and behavioral logic.
- Develop and configure agent personas, goals, and behavioral logic.
- Implement long-term and short-term memory mechanisms for agents, including vector databases and knowledge graphs.
- Integrate external tools, APIs, and data sources for agents to interact with the environment.
- Develop and manage prompts, few-shot examples, and fine-tuning strategies for large language models (LLMs) used by agents.
- Implement decision-making processes and planning capabilities for autonomous agents.
- Utilize orchestration patterns for managing agent interactions and workflows.
Deploy and Manage Agentic AI SolutionsDeploy agentic AI solutions to cloud platforms (e.g., Azure Kubernetes Service, Azure Container Apps).
- Deploy agentic AI solutions to cloud platforms (e.g., Azure Kubernetes Service, Azure Container Apps).
- Implement continuous integration and continuous deployment (CI/CD) pipelines for agentic AI systems.
- Monitor agent performance, resource utilization, and operational health using appropriate tools.
- Establish logging, tracing, and debugging strategies for multi-agent interactions.
- Implement security best practices for agentic AI solutions, including access control and data privacy.
- Manage model versions, agent configurations, and tool integrations in production.
Evaluate and Optimize Agentic AI PerformanceDefine and measure key performance indicators (KPIs) for agentic AI solutions (e.g., task completion rate, efficiency, user satisfaction).
- Define and measure key performance indicators (KPIs) for agentic AI solutions (e.g., task completion rate, efficiency, user satisfaction).
- Design and execute testing strategies for agentic systems, including unit, integration, and end-to-end testing.
- Analyze agent behavior and decision-making processes to identify biases and suboptimal performance.
- Implement feedback loops and human-in-the-loop strategies for continuous improvement of agents.
- Optimize agent performance through prompt engineering, model selection, and resource allocation.
Govern and Secure Agentic AI SolutionsEstablish governance frameworks for agentic AI, including policies for agent autonomy and decision-making.
- Establish governance frameworks for agentic AI, including policies for agent autonomy and decision-making.
- Ensure compliance with relevant regulations and industry standards (e.g., GDPR, HIPAA) for data handled by agents.
- Implement robust security measures to protect against agent manipulation, data breaches, and adversarial attacks.
- Develop strategies for auditing agent actions and decisions to ensure transparency and accountability.
- Manage risks associated with agentic AI, including unintended consequences and ethical dilemmas.
- Design mechanisms for human oversight and intervention in agentic AI systems.
Find your DoD 8140 pathway
Explore how this training may align to DoD 8140 work roles and proficiency levels.
About this course
This advanced certification validates an individual's expertise in designing, implementing, and managing sophisticated agentic AI solutions tailored for complex business environments. The Agentic AI Architect course delves into the principles of autonomous AI agents, multi-agent systems, and their integration with existing enterprise architectures to drive strategic business outcomes. Participants will master the lifecycle of agentic AI solutions, from conceptualization and ethical considerations to deployment, monitoring, and optimization, ensuring robust, secure, and compliant implementations within a DoD context.
Training alone does not establish DoD 8140 qualification. Confirm position-specific requirements with your organization.