AI
AI for Architects
AI for Architects is a three-day intensive program designed for architects and technology leaders who must design and sustain enterprise-grade AI solutions. This course goes beyond ML theory to focus on the architectural building blocks of modern AI systems, with a particular emphasis on agentic AI patterns.
Participants will explore agent and multi-agent architectures, learn how to leverage frameworks such as the Model Context Protocol (MCP), and evaluate orchestration approaches that enable complex AI systems to collaborate, scale, and evolve. The course also addresses the practical realities of AI in production, including data pipelines, training vs. inference trade-offs, observability, security, and compliance.
By the end of the course, attendees will be able to confidently evaluate and design AI-driven architectures that integrate seamlessly with enterprise environments while balancing innovation, cost, and governance.
Duration
3 days
Audience
Software, System, and Solution Architects, Tech Leadership, and Senior AI staff.
prerequisites
- Some technology architecture experience
- Familiarity with typical development and operational tools/environments like Linux, Git, Containers, CI/CD and so on.
- Some exposure to AI/ML concepts is helpful but not required.
Upon completing this course, participants will be able to:
- Understand the full AI solution lifecycle, from data acquisition and training to deployment and ongoing operations
- Evaluate architectural trade-offs across model training, inference, scale, and cost
- Design systems that incorporate AI agents, multi-agent collaboration, and orchestration frameworks
- Apply DevOps, CI/CD, and GitOps principles to AI workloads, ensuring repeatable and scalable delivery
- Integrate observability, governance, and monitoring practices to manage drift, data quality, and performance
- Architect secure and responsible AI systems that address privacy, compliance, and ethical considerations
- Anticipate Day 2 challenges, including model lifecycle management, versioning, and integration with enterprise platforms
Day 1: AI Software & Agentic Architectures
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- AI Architecture Overview – Patterns, reference models, and integration with enterprise systems
- Training & Inference – Data pipelines, model development, serving, and scaling
- Agent Architectures – Foundations of AI agents, tools, and context management
- Multi-Agent Collaboration – Orchestration, coordination, and emerging standards
Day 2: Platforms, CI/CD, and Orchestration
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- AI Platform Tooling – Model registries, orchestration engines, and agent frameworks
- AI CI/CD – Automating training, testing, deployment, and rollback
- GitOps for AI – Declarative operations for ML and agent-based systems
- Observability & Monitoring – Tracking performance, drift detection, and behavior of agents
Day 3: AI Day 2 Operations & Governance
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- AI Security – Protecting data, models, and multi-agent systems from threats
- AI Privacy & Responsible AI – Fairness, bias, compliance, and ethical design
- Lifecycle Management – Versioning, retraining, and managing evolving agent behaviors
- Governance & Strategy – Organizational adoption, cost management, and long-term sustainability
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.