In the “LLM Theory and Building AI Applications” stage, you will learn about Large Language Models (LLM) and other types of AI models, including GPT and open-source models. You will gain knowledge of the basics of Prompt Engineering, including techniques such as Few Shots Prompting, Chain of Thought and React Prompting. Additionally, you will go through the LangChain installation process and create your first “Hello World” in this environment. This stage of the course will provide you with a solid foundation for creating and using advanced AI applications.

In the “LangChain Basics” stage, you will learn to create AI applications, starting with creating a document-based chat. You will learn RAG (Retrieval-Augmented Generation), which will help you understand how AI uses information from various sources. Then you will deepen your knowledge of embeddings, DocumentLoader and Chroma, which is crucial for creating vector databases. You will also learn how to use RetrievalQA Chain to effectively transfer knowledge to AI. Finally, you will implement a simple chat interface in Python using Gradio, which will allow you to practically apply what you have learned.

In the “AI Agents in LangChain” stage, you will learn to build AI applications, such as an AI diet application, using React to prompt and perform tasks. You will also integrate with external websites and learn to create user interfaces in Python using Streamlit, which will allow you to create more interactive and functional AI applications.