The Claude Certified Architect – Foundations course is designed for developers, solution architects, AI engineers, and technical professionals who want to build production-ready AI solutions using Anthropic’s Claude ecosystem.
Throughout the course, participants will learn how to design intelligent AI workflows, integrate Claude through APIs, build modular AI applications using the Model Context Protocol (MCP), and automate development processes with Claude Code. The program combines theory with hands-on practical exercises, providing the knowledge needed to architect reliable, scalable, and secure AI-powered solutions.
Upon completion, participants will understand how to select the appropriate Claude models, design agent-based architectures, manage context efficiently, integrate external tools and services, and implement AI applications following industry best practices.
Module 1 – Introduction to Agent Skills
Learn how to create and manage reusable Claude Skills that help automate repetitive tasks and ensure consistent AI-assisted workflows. This module introduces the concept of Skills and explains how they differ from other Claude Code customization methods, such as CLAUDE.md, hooks, and subagents. Participants will learn how to create custom Skills, configure them for specific tasks, manage permissions, and optimize context usage for better performance. The module also covers organizing Skill libraries, sharing Skills across teams and repositories, integrating them into development workflows, and troubleshooting common issues. By the end of this module, participants will be able to build reusable AI capabilities that improve productivity, maintain coding standards, and simplify collaboration across projects.
Module 2 – Building with the Claude API
Develop the practical skills needed to integrate Claude into real-world applications using the Claude API. Starting with API authentication and basic requests, this module progresses to advanced implementation techniques, including multi-turn conversations, streaming responses, structured outputs, prompt engineering, and systematic evaluation. Participants will learn how to extend Claude with custom tools, implement Retrieval-Augmented Generation (RAG) solutions, integrate external services through the Model Context Protocol (MCP), and design scalable AI workflows and autonomous agent architectures. The module emphasizes production-ready implementation patterns, enabling participants to build secure, reliable, and maintainable AI-powered applications suitable for enterprise environments.
Module 3 – Introduction to Model Context Protocol (MCP)
Explore the Model Context Protocol (MCP) and discover how it simplifies communication between Claude and external applications, services, and data sources. This module explains the client-server architecture of MCP and demonstrates how to build both MCP servers and clients using Python. Participants will learn how to expose tools, resources, and prompts without manually creating complex integrations, making AI applications more modular and scalable. The course also covers testing, debugging, asynchronous communication, resource management, and best practices for implementing MCP in production environments. Through hands-on exercises, participants will gain practical experience connecting Claude to external systems while building flexible AI solutions that are easier to maintain and expand.
Module 4 – Claude Code in Action
Learn how to configure, automate, and manage Claude Code for advanced software development workflows. This module focuses on moving beyond simple prompts to long-running, autonomous AI-assisted development processes. Participants will learn how to configure Claude using CLAUDE.md, Skills, hooks, and permission settings, ensuring consistent and reliable behavior across projects. The module also explores workflow automation through scheduled tasks, headless execution, GitHub integration, and managed code reviews. In addition, participants will learn techniques for verifying AI-generated results, monitoring autonomous executions, and packaging reusable configurations for team-wide adoption. By the end of the module, participants will be able to build efficient, scalable, and trustworthy development workflows powered by Claude Code.
This course is designed for professionals who want to build, integrate, and deploy AI-powered solutions using Anthropic’s Claude ecosystem, including:
- Software Developers
- AI Engineers
- Solution Architects
- Backend Developers
- Technical Consultants
- DevOps Engineers
- Anyone building AI-powered applications with Claude
Upon successful completion of the course, participants will receive a Semos Education Certificate of Completion, recognizing their achievement and the knowledge gained throughout the training.
Optional International Certification
Participants who wish to validate their expertise through an internationally recognized credential may choose to take the official Claude Certified Architect – Foundations (CCAF) certification exam.
The exam is optional and not included in the course fee. The certification exam fee is paid separately.
Successful candidates earn the Claude Certified Architect – Foundations (CCAF) credential, demonstrating their ability to design and implement AI solutions using Anthropic’s Claude platform.
Skills Validated
The CCAF certification validates the ability to:
- Design AI solutions using Claude models
- Select the appropriate Claude model and deployment platform
- Design agentic and workflow-based AI architectures
- Integrate external tools and services using the Model Context Protocol (MCP)
- Apply prompt engineering techniques and structured output generation
- Configure Claude Code workflows and development environments
- Manage context effectively to improve reliability and performance
- Evaluate AI applications while optimizing cost, quality, and responsible deployment