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Claude Certified Developer Foundations (CCDV-F) Certification Prep

Course Summary

This course prepares hands-on builders to sit for the Claude Certified Developer, Foundations (CCDV-F) exam. Participants will build the engineering judgment that turns a Claude prototype into a system that holds up in production: token and context fundamentals, production-grade prompting and tool use, agent orchestration and memory, Claude Code and MCP integration, evals and security hardening, and packaging work as reusable accelerators. The course follows the five domains tested on the CCDV-F exam and closes with hands-on labs and a review of exam objectives and format.

Prequisites:

To get the most out of this session, participants should have:

  • Hands-on familiarity with Claude.ai, Claude Code, and the Claude platform
  • Working experience building integrations against the Claude API and SDKs
  • Completion of AI Fluency: Framework & Foundations, or working knowledge of the AI Fluency competencies
  • Working knowledge of MCP servers, tools, and transports
  • Working understanding of what Claude can and cannot reliably do
  • A development environment with Node.js or Python, a code editor, and API/Claude Code access
Purpose
Prepare for the Claude Certified Developer Foundations (CCDV-F) exam
Audience
  • Hands-on builders who write production code, build agents, run evals, and decide whether a customer's code makes it to production
  • Developers and solutions engineers integrating Claude via the API, SDKs, or Claude Code into real applications
  • Teams preparing to sit for the Claude Certified Developer, Foundations (CCDV-F) exam
Role
Software Developers | AI/ML Engineers
Skill level
Intermediate
Style
Lecture | Hands-on Activities | Labs
Duration
2 days
Related technologies
AI/ML | Python | Claude Code

 

Learning Objectives
  • Explain how Claude works at the level that affects engineering decisions: tokens, the context window as a fixed budget, sampling and non-determinism, model tiers, and SDK versus REST access patterns
  • Write production-ready prompts using system prompts, XML, few-shot, and constraints, and diagnose why a prompt underperforms when first-pass results miss the mark
  • Define and implement tool schemas, construct the tool-use loop, and manage extended thinking across multi-turn work
  • Build a production agent with the right orchestration, memory scope, and human-in-the-loop checkpoints for irreversible actions
  • Run Claude Code under a permission model, give it durable project context, package workflows as Skills and plugins, and connect Claude to enterprise systems through MCP without leaking credentials
  • Build eval suites that define “done,” create test and tracing layers that catch regressions, and keep a system inside its cost, latency, and reliability budget
  • Secure an integration against prompt injection, untrusted input, and exposed secrets so a deployment survives a security or compliance review
  • Package a working build into a reusable accelerator, choose where a workload runs across platforms, and contribute assets back into shared infrastructure

What you'll learn:

In this Claude Certified Developer Foundations (CCDV-F) Certification Prep course, you'll learn:

Domain 1: Agents and Workflows

  • Choose between a workflow and an agent based on task requirements
  • Design manager/supervisor hierarchies and apply subagents
  • Build agents using the Claude Agent SDK and custom agent loops
  • Select an agent deployment model and apply hooks for deterministic actions
  • Apply agent design patterns, including tool-use loops, memory, and context management
  • Evaluate agentic frameworks (e.g., LangGraph, PydanticAI) for multi-step workflows

Domain 2: Applications and Integration

  • Translate business requirements into functional and infrastructure requirements
  • Apply systems life cycle concepts to develop and maintain Claude-based systems
  • Apply Claude API mechanics, including messages, tools, streaming, and caching
  • Select between realtime and batch API access patterns
  • Apply core software engineering practices, including REST APIs, JSON, and version control
  • Integrate Claude development into the SDLC and refactoring workflows
  • Design applications that account for how Claude interprets instructions across interfaces
  • Apply content boundaries, schema design, and session hygiene
  • Configure Claude components using CLAUDE.md, settings.json, and version pinning

Domain 3: Claude Code

  • Operate Claude Code components, including Rules, Skills, Commands, and Agents
  • Manage Claude Code sessions using slash commands, headless mode, and auto-mode
  • Configure the CLAUDE.md hierarchy and settings.json for a repository

Domain 4: Eval, Testing, and Debugging

  • Identify error types and select an appropriate recovery strategy
  • Analyze traces to identify failure modes
  • Isolate problems between the integration layer and model output

Domain 5: Model Selection and Optimization

  • Explain foundational LLM concepts: tokens, context windows, sampling, and non-determinism
  • Select model options such as extended thinking and effort levels
  • Apply fundamental prompting techniques: zero-shot, single-shot, and multi-shot
  • Integrate Claude using SDKs that wrap REST APIs and websockets
  • Differentiate use cases for Opus, Sonnet, and Haiku
  • Weigh quality, latency, and cost tradeoffs when selecting a model
  • Track token usage and apply caching techniques to optimize cost

Domain 6: Prompt and Context Engineering

  • Manage the context window and prevent context drift and bloat
  • Apply context isolation using subagents or multi-step workflows
  • Apply prompt engineering principles, including few-shot examples and output constraints
  • Iteratively refine and sanitize prompts and inputs
  • Apply structured output patterns and validate Claude's responses
  • Apply defensive parsing and skepticism toward confident output

Domain 7: Security and Safety

  • Apply security best practices, including prompt injection and jailbreak defense
  • Prevent data leakage and apply appropriate PII handling
  • Layer guardrails using secure-by-design principles, including least privilege
  • Use hooks to prevent destructive actions
  • Manage secrets, credentials, and API keys across environments
  • Apply identity validation and authorized-access monitoring

Domain 8: Tools and MCPs

  • Implement tool use and function calling for external systems
  • Apply tool usage patterns, including client-side vs. server-side and approval patterns
  • Apply tool set construction and error-handling best practices
  • Author and deploy MCP servers, including tools, resources, and prompts
  • Apply MCP communication patterns, including stdio and client-server design
  • Weigh tradeoffs among built-in tools, custom tools, Skills, and MCPs
  •    

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