About this Course
This specialization introduces you to building intelligent agentic AI systems using modern frameworks such as LangChain, LangGraph, and the Model Context Protocol (MCP). It is designed for developers and AI engineers who want to move beyond single-prompt interactions and build dependable, multi-step AI workflows. You’ll start with the foundations of Agentic AI, learning how agents reason, use tools, and manage context. You’ll then apply prompt engineering, context design, and LCEL workflows to build modular pipelines and intelligent agents. As you progress, you’ll design agents with memory, tools, and structured outputs, and build stateful and multi-agent systems capable of handling complex tasks. The specialization concludes with advanced agent architectures, observability, evaluation, and system-level integration. By the end of this specialization, you will be able to: Explain how intelligent agents are built using LangChain and LangGraph Apply tools, memory, and reasoning to design multi-step agent workflows Design stateful and multi-agent systems to solve complex use cases Evaluate and improve agent behavior using observability and feedback techniques This specialization is ideal for developers and AI engineers with basic Python experience who want hands-on skills in modern agent-based AI system design. Join us now and begin your journey to become an Agentic AI expert
What You'll Learn
- Explain operation of agentic AI systems and orchestration patterns
- Implement agent-based AI to automate workflows using tools and memory
- Assess agent workflows to improve reliability and system behavior
- Design intelligent AI systems aligned with responsible AI principles
Prerequisites
- Basic familiarity with the topic and its common terminology
- Readiness to practice through applied exercises or case-based work
Instructors
Edureka