Claude Certified Developer – Foundations (CCDV-F) – Live Training

                 Claude Certified Developer – Foundations (CCDV-F)

     (Master Claude API, Agents, MCP, Prompt & Context Engineering, Claude Code, Security, Evaluation and Production Integration-with Certification Preparation.)

The trainer is also experienced in explaining complex technical concepts such as REST architecture, asynchronous processing, authentication, API integration, testing, deployment, and application development in a clear and practical manner. Students learn how these concepts work together when developing reliable, scalable, and production-ready AI applications.

An experienced Claude Certified Developer and AI Development Trainer with a strong software-development background and hands-on experience building and deploying production-ready applications.  With hands-on experience developing LLM-powered applications using the Claude API, the trainer brings practical knowledge of modern AI development workflows, including Claude Code and MCP (Model Context Protocol). practical expertise in REST APIs, backend development, authentication, testing, deployment, and production API integration, helping learners understand how modern software systems are designed and delivered in real-world environments.

About the Instructor:

Free Demo On:

Indian Timings: 25th October  @ 9 PM – 10 PM (IST)/

U.S Timings: 25th October  @ 11:30 AM – 12:30 PM (EST)/

U.K Timings: 25th October  @ 4:30 PM – 5:30 PM (BST)

Class Schedule:

For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)

For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)

For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)

What will I learn by the end of this course?

•Select a suitable Claude model based on quality, latency, cost and workload requirements.
• Implement streaming, batching, files/content handling and robust error handling.
• Design prompts and context deliberately rather than relying on trial-and-error prompting.
• Build tool-using applications and understand when to use MCP.
• Distinguish deterministic workflows from agentic systems and implement appropriate orchestration.
• Use Claude Code productively within a controlled software-development workflow.
• Design basic evaluation and regression-testing approaches for LLM applications.
• Identify prompt injection, secret exposure, unsafe tool use and untrusted-input risks.
• Reason through CCDV-F-style multiple-choice and multiple-response scenarios.

• 30+ Hours of Live Training along with recorded videos
• 1 Year access to the recorded videos
• Course Completion Certificate

• Once payment is made, no refund will be provided.
• If you do not attend the course, the payment cannot be transferred to another batch.
• Course repetition is not allowed for missed sessions.

Course Syllabus:

 Module 1: — Claude Developer Foundations & Application Lifecycle

• Claude ecosystem overview: claude.ai, Claude Code, API, SDKs and developer workflows
• LLM fundamentals for developers: tokens, context windows, inference, temperature and model behavior
• Claude API mental model: request, response, messages and content blocks
• REST, JSON, authentication and environment configuration
• SDK installation, project structure and first API integration
• Application lifecycle: prototype → test → evaluate → secure → deploy → monitor
•  Developer decision-making: when Claude should solve a task and when conventional code should solve it
•  Hands-on: build a simple Claude-powered application and document its architecture

Module 2: Applications & Integration: Production Claude API

• Messages API request/response mechanics
• System instructions, user messages and assistant turns
• Content blocks and multimodal inputs
• Streaming responses and incremental UI/application handling
• Files and document/image inputs
• Batch processing and asynchronous workloads
• Timeouts, retries, rate limits and error classification
• SDK patterns, exception handling and configuration management
• Idempotency and safe retry thinking
• Session lifecycle and application state
• Third-party/cloud deployment considerations
• Hands-on: build a production-style Claude service with streaming, error handling and logging

 Module 3:Model Selection, Cost, Latency & Optimization

•  How to think about model capability versus workload requirements
•  Claude model families and practical selection criteria
• Quality, latency and cost trade-offs
• Token accounting and context budgeting
• Prompt caching concepts and when caching helps
• Batch versus real-time processing decisions
• Controlling unnecessary context and output
• Model pinning, version awareness and change management
• Optimization patterns for high-volume applications
• Hands-on: benchmark the same task with different model/configuration strategies

 Module 4: Agents & Workflows

• Workflow vs agent: deterministic execution versus autonomous decision-making
• Agent loops and tool-use loops
•  Planning, execution, observation and recovery
• Stop conditions and preventing runaway agents
• Subagents and task delegation
•  Supervisor/manager patterns and return contracts
• State, memory and context-window management
• Human-in-the-loop and escalation patterns
• Hosted versus self-managed agent execution concepts
• Claude Agent SDK concepts and implementation patterns
• Hands-on: build a research or support agent with controlled tool use and escalation

 Module 5: Prompt & Context Engineering

•  Prompt engineering as software engineering
•  Instruction hierarchy and clear task framing
• Zero-shot and few-shot prompting
• Examples, delimiters and structured context
• Prompt templates and reusable prompt components
• Context selection, compression and prioritization
• Managing long conversations and tool-result growth
• Structured output and schema-driven responses
• Reducing ambiguity and improving reliability
• Prompt versioning and regression awareness
• Hands-on: convert an unreliable prompt into a production-ready prompt with structured output

 Module 6: Tools, Function Calling & MCP

• Why tools are needed in Claude applications
• Tool definitions, descriptions and input schemas
• Tool selection and tool-result handling
• Validation, permissions and safe tool execution
• Designing narrow, predictable tools
• Model Context Protocol: purpose, architecture and terminology
• MCP clients, servers, tools, resources and prompts
• Connecting Claude to external systems through MCP
• Authentication and trust boundaries
• Built-in tools vs custom tools vs MCP vs Skills
• Hands-on: create a small MCP server and connect it to a Claude workflow

 Module 7: Security, Safety & Responsible Production

•  Threat model for Claude-powered applications
• Prompt injection and indirect prompt injection
• Untrusted user input and untrusted retrieved/tool data
• Secret and API-key management
• Least privilege for tools and external systems
• Tool abuse and permission boundaries
• Data leakage and sensitive-context handling
• Input/output validation and guardrails
• Human approval for high-impact actions
• Secure logging without exposing sensitive data
• Hands-on: attack and harden the capstone application against common AI security failures

 Module 8: Claude Code + Evaluation, Testing & Debugging

• Claude Code role in the developer lifecycle
• CLAUDE.md and project context
• Rules, Skills, Commands and subagent concepts
• Session management and controlled automation
• Using Claude Code for coding, refactoring, testing and documentation
• Headless/automated workflows and permission awareness
• Evaluation fundamentals: what should be measured?
• Deterministic tests vs model-based evaluations
• Regression testing for prompts and model changes
• Debugging: API failure vs tool failure vs prompt failure vs model-output failure
• Failure reproduction and observability
• Hands-on: use Claude Code to modify the capstone, then run a small evaluation/regression suite

 Module 9: CCDV-F Certification Preparation + Capstone

•  Full review of all eight CCDV-F domains
• Domain-weighted revision strategy
• Scenario-based decision questions
• Multiple-choice versus multiple-response strategy
• Distractor analysis and requirement extraction
• API/integration troubleshooting scenarios
• Model-selection and optimization scenarios
• Agent/tool/MCP/security scenarios
• Timed domain quizzes
• Full mock examination
• Capstone presentation and engineering review
• Personal weak-area remediation plan and final exam readiness checklist

Practical Labs & Capstone : 
Recommended capstone:  Enterprise Support Intelligence Agent

Learners progressively build one realistic application rather than completing unrelated toy demos. The application receives a user request, uses Claude for reasoning and structured output, calls controlled tools, optionally connects through MCP, maintains relevant context, handles errors, records evaluation data and enforces security boundaries.

• Basic Claude API integration

• Streaming and structured responses

• Model selection and cost optimization

• Tool use and external data

• Agent workflow and escalation

• MCP integration

• Security hardening

• Evaluation, regression tests and debugging

• Claude Code-assisted development and final deployment design

Additional Mini-Labs

• Learners progressively build one realistic application rather than completing unrelated toy demos

• Document summarization with controlled context

• Structured invoice/ticket extraction

• Tool-using API assistant

• Multi-step research workflow

• Prompt-injection attack and defense exercise

• Model/cost comparison exercise

• MCP server for a simple internal knowledge or utility service

• LLM regression test suite

Suggested Course Promise

• Certification preparation for professionals targeting CCDV-F.
• Practical Claude development for learners who do not intend to take the exam.
• Hands-on implementation rather than prompt-only training.
• Designed for experienced IT professionals, with fundamentals included where required.
• One evolving enterprise capstone connecting the major concepts.

Recommended Duration Options

How can I enroll for this course?

Enroll For Free Demo