Fundamentals of AI Agents Using RAG and LangChain

Unlock the power of Large Language Models (LLMs) and take your AI engineering skills to the next level. This course, Fundamentals of AI Agents Using RAG and LangChain, is designed for developers, data scientists, and AI enthusiasts who want to build production-ready AI systems.

You’ll gain hands-on expertise in two core areas:

1. RAG Framework (Retrieval-Augmented Generation) Learn how to combine LLMs with external knowledge sources to deliver accurate, up-to-date, and context-aware AI responses. Master techniques to connect vector databases, optimize retrieval pipelines, and minimize hallucinations in real-world AI applications.

2. Prompt Engineering with LangChain Dive deep into LangChain, the industry-leading framework for building AI agents and applications. Discover how to design effective prompts, chain together LLM workflows, integrate APIs, and orchestrate intelligent multi-step reasoning.

By the end of this course, you’ll have the technical foundation to:

• Build scalable AI agents capable of reasoning, retrieving, and acting.
• Deploy LLMs that solve real business problems with precision.
• Apply RAG and LangChain to enterprise-grade projects in search, chatbots, knowledge assistants, and automation.

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Prerequisites

To maximize learning, you should have:

• Basic knowledge of Python programming
• Familiarity with machine learning or NLP concepts (helpful but not mandatory)
• Understanding of APIs and databases (a plus for building retrieval pipelines)
• Enthusiasm to explore AI/LLM applications

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Where It Can Be Applied

Skills from this course can be applied in:

• Enterprise Search Systems – build knowledge retrieval assistants powered by LLMs
• Customer Support Chatbots – create AI agents that give context-aware, human-like answers
• Knowledge Management Tools – connect company data to AI for decision support
• Financial & Legal Document Analysis – automate insight extraction with higher accuracy
• Healthcare Assistants – enable medical AI agents that retrieve evidence-based answers
• Education & EdTech – design personalized tutoring systems driven by LangChain
• Automation & Productivity Tools – integrate AI into workflows to boost efficiency

With AI engineers in record demand, these skills will set you apart and prepare you for high-impact roles in the rapidly growing GenAI job market.