Claude Certified Architect - Foundations (CCA-F) Full Prep

About this course

THE MAGNUM (4.8) OPUS OF THE CLAUDE CCA-F EXAM PREPARATIONThe Claude Certified Architect - Foundations, or CCA-F, is the first professional certification focused on Anthropic's entire ecosystem and modern AI architecture.Passing this certification will require a lot more than just knowing how to write prompts. As a candidate, you are expected to understand how production-grade Claude systems are designed, orchestrated, validated, and scaled across real-world applications.It's about being a true Claude-based AI solution architect. More than that, a production-grade Claude-based AI solution architect.This course was built specifically to make you into that.Over more than 12 hours of content, you'll learn everything about the five certification domains (or, as I call them, the Five Layers), understanding how they connect together in production systems, and master the architectural principles that appear repeatedly.Along the way, you'll have a full practice exam, role plays, Labs (for UB Pro clients), and quizzes to consolidate your knowledge every step of the way.The course follows the complete CCA-F blueprint:Agentic Architecture & Orchestration (the Agentic Layer)Tool Design & MCP Integration (the Tool Layer)Claude Code Configuration & Workflows (the Workflow Layer)Prompt Engineering & Structured Output (the Prompt Layer)Context Management & Reliability (the Context Layer)We'll start by covering the certification itself, including the exam structure, tested competencies, and from there, we'll progressively explore every domain in detail. We'll close out the course with a recap of the most important patterns, the common antipatterns to avoid, and 10 key takeaways that summarize the certification.Along the way, you'll study both the best

Course objectives

• prepare for the Claude Certified Architect - Foundations (CCA-F) certification exam
• explore the interconnectedness of different AI architectural layers
• summarize key takeaways and patterns for AI architecture