The Claude AI Certification Course helps professionals understand and apply Claude AI for real-world tasks and business use cases. It introduces key concepts such as prompt engineering, document analysis, and automation. It also provides practical knowledge to improve productivity, decision-making, and efficiency. The course covers the Claude API, prompt engineering for developers, tool use / function calling, structured output, streaming, and the fundamentals of the Claude Agent SDK. Learners build real integrations and learn the patterns that make Claude applications reliable in production. This training enhances skills in prompt design, content generation, and workflow automation. It enables professionals to extract insights, improve communication, and streamline processes. Learners gain practical knowledge to increase efficiency and support data-driven decisions.

Course Objectives:

In this course, you will learn to:

• Describe the Claude model family and choose the right model for a task
• Use the Claude apps and Projects to organize context and knowledge
• Write clear, structured prompts that produce reliable results
• Apply prompt techniques such as roles, examples, and step-by-step guidance
• Understand agentic AI concepts and how Claude uses context and tools
• Recognize Claude's capabilities, limitations, and safe-use boundaries
• Apply responsible-AI and data-handling best practices
• Use Claude for summarization, drafting, analysis, and everyday knowledge work
• Authenticate and call the Claude API using the official SDKs
• Engineer prompts programmatically with system prompts and messages
• Enforce structured (JSON) output and validate model responses
• Stream responses and handle latency, errors, and retries
• Use the Claude Agent SDK to build simple agentic workflows
• Apply prompt caching and manage the context window efficiently
• Integrate Claude into backend and application code responsibly

Course content

Introduction to Claude & Agentic AI

• What Claude is and how large language models work
• Agentic AI vs. traditional chatbots and prompt-only tools
• The Claude model family and model selection basics
• The Claude apps: web, desktop, mobile, and Projects
• Lab: up Claude and create your first Project
• Lab: Compare model responses on the same task

Getting Started with the Claude API

• Claude Developer Platform and authentication
• The Messages API: requests, responses, and roles
• The Claude model family and choosing a model
• Parameters: temperature, max tokens, stop sequences
• Lab: Make your first API call
• Lab: Compare parameters and model behaviour

Prompting Fundamentals

• Anatomy of an effective prompt
• Roles, context, task, and format (structured prompting)
• Giving examples and step-by-step instructions
• Iterating and refining prompts for better output
• System prompts, user/assistant turns, and message design
• Few-shot prompting and examples in code
• Prompt templates and reusable patterns
• Prefilling responses and controlling tone/format
• Lab: Rewrite a weak prompt into a structured one
• Lab: Use examples to control output format

Working with Context & KnowledgeSet

• How Claude uses context and the context window
• Uploading files and grounding responses in your data
• Organizing knowledge with Projects
• Understanding hallucinations and how to reduce them
• Lab: Build a knowledge Project and query your documents

Everyday Productivity with Claude

• Summarization, drafting, and rewriting
• Data extraction and simple analysis
• Brainstorming, planning, and decision support
• Building reusable prompt templates
• Lab: Automate a recurring writing task
• Lab: Extract structured data from a document

Responsible & Safe Use of Claude

• Claude’s capabilities and limitations
• Responsible-AI principles and safe usage
• Data privacy, confidentiality, and appropriate use
• Verifying, reviewing, and fact-checking AI output
• Lab: Identify and correct unsafe or low-quality outputs

Structured Output & Reliability

• Enforcing JSON and schema-conformant output
• Validation and retry loops
• Programmatic enforcement vs. prompt-based guidance
• Handling edge cases and malformed responses
• Lab: Extract structured JSON with validation and retries

Tool Use & Function Calling

• Defining tools and JSON schemas
• The tool-use request/response loop
• Chaining multiple tools and parallel calls
• Writing tool descriptions Claude can use reliably
• Lab: Build a weather/lookup tool integration
• Lab: Chain tools to complete a task

Streaming, Caching & Error Handling

• Streaming responses for responsive UX
• Prompt caching with cache breakpoints
• Rate limits, retries, and backoff
• Token counting and context-window management
• Lab: Add streaming to an app
• Lab: Apply prompt caching to reduce cost/latency

Introduction to the Claude Agent SDK

• Agentic loops: observe–think–act–respond
• Building a simple agent with the Agent SDK
• Adding tools and guardrails to an agent
• Responsible AI and secure API usage
• Lab: Build a minimal tool-using agent with the Agent SDK

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