Develop your own gen AI applications with Python! Get an introduction to generative AI, NLP models, LLMs, and LMMs-and then dive into pretrained models with Hugging Face. Work with LLMs using Python with the help of tools like OpenAI and LangChain. Get step-by-step instructions for using vector databases and retrieval-augmented generation. With information on agentic systems and AI application deployment, this guide has everything you need to become a gen AI master! Large Language Models, Set up LLMs and then learn how to apply your models using Python. Walk through the available tools: OpenAI, Meta's Llama model family, Groq, and open-source LLMs. Work with prompt templates, chains, and more. Vector Databases, Create and use vector databases to store and query large collections of documents. Master all aspects of the pipeline: loading a raw document, processing it, and storing it in your vector database.

Agentic Systems, Use AI models to build agents that act autonomously to achieve their goals. Discover the different frameworks for this task: Lang-Graph, AG2, CrewAI, OpenAI Agents, and Pydantic AI. Highlights include, Natural language processing (NLP) models, Large language models (LLMs), Pretrained models, Prompt engineering, Vector databases, Retrieval-augmented generation (RAG), Agentic systems, OpenAI, LangChain, Hugging Face.