Agentic AI Engineering with Hugging Face & LangChain

Build intelligent, autonomous AI applications with Hugging Face and LangChain in this practical, hands-on Agentic AI course. Learn how modern AI agents can understand instructions, reason through tasks, use tools, interact with external data, and complete multi-step workflows with minimal human intervention.

This course introduces the fundamentals of Agentic AI and gradually takes you into practical implementation using Hugging Face models and LangChain. You’ll learn how to work with open-source and transformer-based models from the Hugging Face ecosystem and connect them with LangChain to build powerful AI-driven applications.

You’ll explore essential concepts such as LLMs, prompts, chains, agents, tools, memory, retrieval-augmented generation (RAG), embeddings, vector databases, and multi-step agent workflows. Through hands-on examples and projects, you’ll understand how to design AI agents that can interact with APIs, retrieve information, process documents, and make decisions based on user requirements.

The course also focuses on building practical Agentic AI solutions rather than learning concepts in isolation. You’ll gain experience creating intelligent workflows, integrating different tools and models, and developing applications that can solve real-world problems.

Whether you are a Python developer, AI enthusiast, software engineer, data professional, or someone looking to enter the rapidly growing field of Agentic AI, this course provides a structured path to building modern AI agent applications with Hugging Face and LangChain.

By the end of the course, you’ll have the knowledge and practical skills to design, develop, and experiment with your own Agentic AI applications using open-source AI models and LangChain