3-Day Live Instructor-Led Training
Hands-on Labs
After-Course Instructor Coaching Included
Exam Prep: Claude Certified Developer (CCDV-F)
Course 1357
- Duration: 3 days
- Language: English
- Level: Intermediate
This course gives you the skills to build and deploy production-grade AI-enabled applications that leverage Anthropic’s Claude platform to serve both internal organization staff and external partners and customers. You will see how to translate technical requirements into production-ready, cost-effective AI-enabled applications using API integration, Claude Tools and Skills, MCP Servers, prompt engineering, and context management. By the end of this course, you will have hands-on experience in building secure AI applications that respect privacy constraints.
You’ll also have the strategies and tools both to evaluate your applications for reliability before deployment and to support extending, enhancing, and debugging your applications after deployment. This course also helps prepare you for the Claude Certified Developer Foundations certification exam.
Claude Developer Exam Prep Course Delivery Methods
In-Person
Online
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Claude Developer Exam Prep Course Information
Course Benefits
- Build agents and workflows using the Claude Agent SDK and agentic frameworks to integrate AI into both Line-of-Business and customer-facing applications
- Apply context engineering to control model behavior and prevent context drift
- Evaluate your AI-enabled application both in development and in production
- Optimize your application for cost and responsiveness
- Apply secure-by-design principles to implement effective guardrails that ensure both security and privacy
- Author Claude Skills, custom tools, plugins, and MCP servers
Prerequisites
Experience in building business applications in any platform.
Claude Developer Exam Prep Course Outline
Module 1: Architecting AI-Enabled Applications
- Choosing between workflows, single agent, and agent/subagent designs
- Building agents with the Claude Agent SDK, custom agent loops and harnesses
- Choosing deployment strategies: Self-hosted vs. Anthropic-hosted
- Implement agent design patterns: Tool-use loops, subagents, memory, and context-window management
- Selecting among agentic abstraction frameworks (Strands, LangGraph, PydanticAI)
- Designing applications for Claude Code, Claude Desktop, claude.ai, Claude API, and Claude SDKs
Module 2: Model Selection and Optimization
- Understanding LLMs, tokens, context windows, long with the impact of non-determinism, and next-token generation
- Selecting between fast mode, extended thinking, and adaptive thinking modes
- Working with effort levels
- Deciding when to use zero-shot, single-shot, and multi-shot prompting
- Picking the right model of Opus, Sonnet, and Haiku
- Exploiting cost management techniques beginning with token usage tracking, cost modeling, and caching
Module 3: Integrating Claude into Applications
- Turning application requirements into AI solutions
- Building with messages, tools, streaming, vision, and thinking
- Configuring Claude system components, including CLAUDE.md files, settings.json, model version pinning, prompt versioning, and plugin dependencies
- Implementing error handling, including effective recovery strategies
- Debugging with trace analysis to identify failure modes and isolate problems
- Integrating REST and Web sockets APIs
- Combing Claude’s Messages API with batch API to reduce costs
Module 4: Prompt and Context Engineering
- Managing the context window
- Preventing context drift and bloat with output pruning and compaction
- Isolating context with subagents and multi-step workflows
- Engineering prompt: Principles and methods
- Improving processing with system prompts. user prompts, and constrained output
- Handling output with established patterns and techniques to produce, validate, and consume output
- Increasing output confidence through structured output patterns, response validation, defensive parsing, and skepticism
Module 5: Accelerating Development with Claude Code
- Exploiting Claude Code Rules, Skills, Commands, Agents, Agent Memory, and session management
- Creating built-in and custom slash commands
- Operating in headless, streaming mode, and auto-mode
Module 6: Extending Applications with Tools and MCP Servers
- Understanding the tradeoffs among built-in tools, custom tools, Skills, and MCP servers
- Best practices for constructing tools and toolsets
- Writing effective tool descriptions
- Picking the right tool usage pattern (agentic harness dispatch, selecting between client-side and server-side tools, choosing approval patterns)
- Configuring for external system interaction
- Best practices in MCP server development and communication when integrating external resources
Module 7: Security and Safety
- Ensuring data privacy and applying security best practices
- Mitigating prompt injection and sanitizing prompts
- Defending against jailbreaks
- Ensuring authentication, authorization, confidentiality, privacy, and integrity.
- Implementing safe and responsible deployment practices with content policy and guardrail layering
- Implementing secure-by-design principles, including using hooks for guardrails and other safety controls
- Managing secrets, credentials, and API keys across development and production environments
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Claude Developer Exam Prep Course FAQs
Candidates should have experience with software development and a working knowledge of generative AI concepts. Familiarity with Claude APIs, prompt and context engineering, tool use, agents, the Model Context Protocol (MCP), and techniques for testing and evaluating AI applications will also be beneficial.
While self-study can help you become familiar with certification topics, Learning Tree provides a structured, instructor-led experience designed to help you turn concepts into practical skills. You’ll learn from an expert instructor, work through complex topics and real-world scenarios, ask questions in real time, and benefit from a focused learning environment that keeps your preparation on track. The course also helps you identify knowledge gaps and focus on the skills and concepts most relevant to the certification exam—while building practical knowledge you can apply beyond the exam.