Agentic AI Bootcamp with LangGraph,Langchain and MCP
Published 5/2025
Duration: 21h 44m | .MP4 1920x1080, 30 fps(r) | AAC, 44100 Hz, 2ch | 10.9 GB
Genre: eLearning | Language: English
Published 5/2025
Duration: 21h 44m | .MP4 1920x1080, 30 fps(r) | AAC, 44100 Hz, 2ch | 10.9 GB
Genre: eLearning | Language: English
Master LangGraph & LangChain Agentic AI with MCP, Hugging Face Deployment
What you'll learn
- Understand the core concepts of agentic AI and autonomous agents
- Build powerful AI workflows using LangChain and LangGraph
- Design and manage multi-agent systems using the MCP protocol
- Implement memory, state management, and reasoning in agents
- Use Cursor and Claude as clients to interact with MCP agents
- Implement memory, state management, and reasoning in agents
- Integrate tools, APIs, and language models into agent workflows
- Develop a complete end-to-end AI project from scratch
- Deploy your agentic AI application to Hugging Face for real-world use
Requirements
- Python
Description
Unlock the future of AI development with this hands-on bootcamp focused on building intelligent, autonomous systems usingLangGraph,LangChain, andMulti-Agent Control Protocol (MCP). Whether you're a developer, AI enthusiast, or tech entrepreneur, this course will guide you through creating powerfulagentic AI applicationsfrom scratch to production deployment.
In this course, you'll explore how to architectagent-based systemsthat reason, plan, and collaborate using LangChain's powerful framework. You'll dive deep intoLangGraph, an innovative extension enabling graph-based memory, state transitions, and multi-agent orchestration. Learn how to integrateMCPto control agent behavior, communication, and coordination with real-world use cases.
By the end of this bootcamp, you’ll build a completeend-to-end agentic AI projectand deploy it confidently onHugging Face, enabling cloud-based inference and real-time interaction.
What You’ll Learn:
Fundamentals of Agentic AI and the LangChain ecosystem
Building LangGraph-based agents with persistent memory and workflows
Using MCP for managing complex multi-agent systems
Integrating APIs, tools, and language models with LangChain
Full-stack project development: from local prototyping to Hugging Face deployment
Why Take This Course?
This course blendstheory with practical projects, giving you the skills to not only understand butbuild deployable agentic AI systems. You’ll gain confidence working with cutting-edge libraries and frameworks that are shaping the future of LLM applications.
Enroll now and start building the next generation of autonomous AI agents!
Who this course is for:
- Agentic AI Developer
More Info