AI Agent Specialist

The AI Agent Specialist course prepares professionals to lead the next generation of agent-based AI systems—ones that adapt, reason, and align with real-world expectations. This program focuses on the hardest and most critical frontier in intelligent systems: building safe, refined, and continuously evolving agents.

• 5 Hours Live Online Event (Two 2.5 hour sessions)
• 5 Hours of Self-Paced Practicum

As the second of two required courses for the W3CB AI Architect+ Certification, this course goes far beyond architecture and automation. Learners gain hands-on expertise in fine-tuning LLMs, building RLHF feedback loops, conducting adversarial red-teaming, and simulating dynamic environments. From multimodal inputs to memory governance and graph-based reasoning, participants will build agents that not only function—but evolve. The final capstone demonstrates mastery through a fully validated, safe, and intelligent agent system.

Prerequisites

• Completion of AI Systems Architect or equivalent experience
• Comfort with LLMs, prompting, vector stores, and orchestration frameworks
• Experience with APIs and containerized deployment environments preferred

Target Audience

• AI/ML engineers building advanced copilots and agentic workflows
• Senior developers deploying LLMs in sensitive, regulated, or production-grade settings
• AI safety researchers, alignment-focused practitioners, and agent testers
• Product leaders delivering autonomous agents for education, research, or operations
• Enterprise teams scaling multi-modal, multi-step AI agent systems

Learning Objectives

By completing the AI Agent Specialist course, learners will be able to:

• Fine-tune large language models to align with custom domain behaviors
• Implement reinforcement learning from human feedback (RLHF) and agent scoring
• Simulate task environments to test and refine agent workflows
• Design multimodal agents capable of processing text, image, and voice inputs
• Build knowledge graphs and dynamic reasoning paths into agents
• Audit behavior and govern agent memory using versioning and retention logic
• Conduct adversarial safety testing and deploy agents with compliance-aligned safeguards