Build & Test AI Agents, ChatBot, RAG with Ollama & Local LLM
Learn Building and Testing AI Agent, ChatBot, RAG with LangChain and LangSmith using Ollama and Local LLMs and RAGAs
Build & Test AI Agents, ChatBot, RAG with Ollama & Local LLM free download
Learn Building and Testing AI Agent, ChatBot, RAG with LangChain and LangSmith using Ollama and Local LLMs and RAGAs
Build & Test AI Agents, Chatbots, and RAG with Ollama & Local LLMs
This course is designed for complete beginners—even if you have zero knowledge of LangChain, you’ll learn step by step how to build LLM-based applications using local Large Language Models (LLMs).
We’ll go beyond development and dive into evaluating and testing AI agents, RAG applications, and chatbots using RAGAs to ensure they deliver accurate and reliable results, following key industry metrics for AI performance.
What You’ll Learn:
Fundamentals of LangChain & LangSmith
Chat Message History in LangChain for storing conversation data
Running Parallel & Multiple Chains (RunnableParallels, etc.)
Building Chatbots with LangChain & Streamlit (with message history)
Understanding Tools and Tool chains in LLM
Building Tools and Custom Tools for LLM
Creating AI Agents using LangChain
Implementing RAG with vector stores & local LLM embeddings
Using AI Agents and RAG with Tooling while building LLM Apps
Optimizing & Debugging AI applications with LangSmith
Evaluating & Testing LLM applications with RAGAs
Real-world projects & hands-on testing strategies
Assessing RAG & AI Agents with RAGAs
This entire course is taught inside Jupyter Notebook with Visual Studio, providing an interactive, guided experience where you can run the code seamlessly and follow along effortlessly.
By the end of this course, you’ll be able to build, test, and optimize AI-powered applications with confidence!
