This course includes 1,000 high-yield, scenario-based questions carefully distributed to cover the entire syllabus. Every single question comes with elaborate, concise option-by-option explanations—breaking down not just why the right answer is correct, but precisely why every distractor option fails to meet the scenario's architectural or operational constraints.

Comprehensive Coverage of All 8  CCDV-F Exam Domains:

• Domain 1: Applications and Integration (Application design, state management, API streaming, and integration contracts).

• Domain 2: Agents and Workflows (Autonomous agent architecture, multi-step orchestration, and delegation models).

• Domain 3: Tools and MCPs (Model Context Protocol server implementation, tool schemas, and execution validation).

• Domain 4: Claude Code (CLI usage, custom hooks, CLAUDE MD file management, and CI/CD integration).

• Domain 5: Prompt and Context Engineering (Prompt optimization, XML tags, and context window management).

• Domain 6: Model Selection and Optimization (Choosing between Haiku, Sonnet, and Opus based on cost, latency, and quality).

• Domain 7: Eval, Testing, and Debugging (Traceability, error logging, resolving context drift, and MLOps).

• Domain 8: Security and Safety (Preventing indirect prompt injections, enterprise governance, and PII management).

What You Will Learn

• Master all 8 CCDV-F exam domains through 1,000 realistic, scenario-based practice questions.

• Architect scalable AI applications, integrate Claude APIs, handle streaming, and manage conversational state.

• Design autonomous agents and workflows, orchestrating multi-step reasoning and human-in-the-loop gates.

• Build and integrate tools securely using the Model Context Protocol (MCP) and custom API adapters.

• Automate software engineering tasks, codebase navigation, and CI/CD pipelines using Claude Code.

• Optimize model selection (Haiku, Sonnet, Opus) and evaluate outputs using rigorous MLOps testing frameworks.

• Enforce enterprise security, prevent prompt injections, and ensure responsible AI governance protocols.

Requirements

• Basic understanding of software engineering, API integration, and programming (e.g., Python or TypeScript).

• Foundational knowledge of LLM concepts, prompt engineering, and interacting with the Anthropic API.

• No prior certification is required, but hands-on experience building AI applications is highly recommended.

Who This Course Is For

• Software Engineers, AI Developers, and Solutions Architects preparing for the Claude Certified Developer – Foundations (CCDV-F) exam.

• Developers looking to validate their skills in building production-grade applications using the Anthropic API, Claude Code, and MCP.

• Candidates seeking realistic, timed exam simulations with thorough option-by-option explanations to guarantee exam readiness.