Build & Test AI Agents, ChatBot, RAG with Ollama & Local LLM

<div><u style=""><b>Build &amp; Test AI Agents, Chatbots, and RAG with Ollama &amp; Local LLMs Course</b></u></div><div><br></div><div>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).</div><div><br></div><div>The course is fully updated with LangChain v1.0.3</div><div><br></div><div>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.</div><div><br></div><div>What You’ll Learn:</div><div><ul><li><span style="font-size: 1rem;">Fundamentals of LangChain &amp; LangSmith</span></li><li><span style="font-size: 1rem;">Chat Message History in LangChain for storing conversation data</span></li><li><span style="font-size: 1rem;">Running Parallel &amp; Multiple Chains (RunnableParallels, etc.)</span></li><li><span style="font-size: 1rem;">Building Chatbots with LangChain &amp; Streamlit (with message history)</span></li><li><span style="font-size: 1rem;">Understanding Tools and Tool chains in LLM</span></li><li><span style="font-size: 1rem;">Building Tools and Custom Tools for LLM&nbsp;</span></li><li><span style="font-size: 1rem;">Creating AI Agents using LangChain</span></li><li><span style="font-size: 1rem;">Implementing RAG with vector stores &amp; local LLM embeddings</span></li><li><span style="font-size: 1rem;">Using AI Agents and RAG with Tooling while building LLM Apps</span></li><li><span style="font-size: 1rem;">Optimizing &amp; Debugging AI applications with LangSmith</span></li><li><span style="font-size: 1rem;">Evaluating &amp; Testing LLM applications with RAGAs</span></li><li><span style="font-size: 1rem;">Real-world projects &amp; hands-on testing strategies</span></li><li><span style="font-size: 1rem;">Assessing RAG &amp; AI Agents with RAGAs</span></li></ul></div><div><br></div><div>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.</div><div><br></div><div><span style="font-size: 1rem;">By the end of this&nbsp;</span><b>Build &amp; Test AI Agents, ChatBot, RAG with Ollama &amp; Local LLM&nbsp;</b><span style="font-size: 1rem;"><b>course</b>, you’ll be able to build, test, and optimize AI-powered applications with confidence!</span></div>

What you'll learn:

• Running LLMs in Local Machine for development of LLM application
• Understand the power of Langchain for building Local LLM application
• Understand Chain, Prompts, ChatPromptTemplates, ChatMessageHistory
• Building Chatbots with Historical Information with Langchain
• Building RAG application with Vector stores, Embedding and Local LLMs
• Understanding and Building Tools for LLMs
• Building AI Agents with Tooling support for LLMs
• Testing/Evaluating AI Agent & RAG Application with RAGAs