This course contains the use of artificial intelligence.

Build intelligent, autonomous, and enterprise-ready AI systems with Claude Agentic AI in this comprehensive 12-week, hands-on course. Designed for developers, AI engineers, architects, technical leaders, and professionals exploring the future of automation, this course teaches you how to design, build, evaluate, and deploy real-world agentic AI systems using Claude.

Unlike traditional generative AI applications that only respond to prompts, agentic systems can plan tasks, use tools, retrieve information, maintain memory, collaborate with other agents, and take actions toward defined goals. Throughout this course, you will move beyond basic chatbot development and learn how to create practical AI agents, multi-agent systems, and intelligent enterprise workflows.

You will begin by exploring the foundations of Agentic AI vs Generative AI, the Claude ecosystem, Claude models, APIs, tool use, and common agent design patterns. You will then develop advanced skills in Claude prompt engineering, including system prompts, behavioral shaping, structured prompting, XML and JSON output schemas, prompt evaluation, and iterative improvement techniques.

A major focus of the course is tool use and function calling with Claude. You will learn how to create reliable tool schemas, connect agents to calculators, databases, retrieval systems, business APIs, and external services, and build robust tool invocation workflows with validation, error handling, and retries.

The course also covers Retrieval-Augmented Generation, commonly known as RAG, including document chunking, embeddings, vector databases, retrieval pipelines, and methods for evaluating retrieval quality. You will combine Claude with enterprise knowledge sources to build accurate, context-aware assistants and internal knowledge agents.

As your systems become more advanced, you will implement AI agent memory, session state, persistent storage, vector memory, and symbolic memory. You will design single-agent systems using planning, task decomposition, reasoning loops, observability, logging, and recovery mechanisms.

You will then progress into multi-agent architecture, exploring supervisor-worker models, specialized agent roles, swarm patterns, agent communication, conflict resolution, and coordination strategies. You will compare popular AI orchestration frameworks, including LangChain, LlamaIndex, and custom workflow approaches, while learning when to use deterministic workflows versus autonomous agents.

Real-world enterprise applications are integrated throughout the course. You will explore AI copilots, customer support automation, internal knowledge assistants, software engineering agents, and intelligent business workflow automation.

Security and governance are also central to the curriculum. You will learn about AI governance, prompt injection, sensitive data leakage, access control, guardrails, auditing, compliance, and enterprise risk management.

Finally, you will learn how to deploy and scale Claude-powered agents using APIs, serverless architectures, containers, monitoring, cost optimization, and human-in-the-loop controls. The course concludes with a capstone project in which you will design, build, test, evaluate, and present a complete enterprise agentic AI solution.

By the end of this course, you will have the practical skills and architectural knowledge needed to build reliable, secure, scalable, and production-ready Claude AI agents for real-world applications.