Skip to main content

🧠🤖 Build & Test AI Agents, ChatBots, and RAG with Ollama & Local LLM

💡 Note

All the courses are available on Udemy, and they almost always have a coupon code available.
For discounts, please feel free to reach out at karthik@techgeek.co.in.

🎯 Course Link:
Build & Test AI Agents, ChatBots, and RAG with Ollama & Local LLM

📚 Course Description​

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
    Get a solid foundation in building and testing LLM-based applications.

  • 💬 Chat Message History in LangChain
    Learn how to store conversation data for chatbots and AI agents.

  • ⚙️ Running Parallel & Multiple Chains
    Master advanced techniques like RunnableParallels to optimize your LLM workflows.

  • 🤖 Building Chatbots with LangChain & Streamlit
    Create chatbots with message history and an interactive UI.

  • 🛠️ Tools & Tool Chains in LLMs
    Understand the power of Tooling, Custom Tools, and how to build Tool Chains for AI applications.

  • 🧑‍💻 Creating AI Agents with LangChain
    Implement AI agents that can interact dynamically with RAG applications.

  • 📚 Implementing RAG with Vector Stores & Local Embeddings
    Develop robust RAG solutions with local LLM embeddings.

  • 🔧 Using AI Agents & RAG with Tooling
    Learn how to integrate Tooling effectively while building LLM Apps.

  • 🚦 Optimizing & Debugging AI Applications with LangSmith
    Enhance your AI models and applications with LangSmith's debugging and optimization tools.

  • 🧪 Evaluating & Testing LLM Applications with RAGAs
    Apply hands-on testing strategies to validate RAG and AI agent performance.

  • 📊 Real-world Projects & Assessments
    Gain practical experience with RAGAs and learn to assess the quality and reliability of AI solutions.

🎯 Learning Experience​

This entire course is taught inside a Jupyter Notebook with Visual Studio, offering an interactive, guided experience where you can run the code seamlessly and follow along effortlessly.

By the end of this course, you’ll have the confidence to build, test, and optimize AI-powered applications with ease!