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

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:::info 💡 **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](mailto:karthik@techgeek.co.in)**.

🎯 **Course Link:**  
[Build & Test AI Agents, ChatBots, and RAG with Ollama & Local LLM](https://www.udemy.com/course/build-ai-agent-chatbot-rag-langchain-local-llm/)
:::

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## 📚 **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**.

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### 🚀 **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**.

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## 🎯 **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!