Full stack generative and Agentic AI with python

This comprehensive guide on generative and agentic AI offers an immersive pathway for Python developers to transition into the cutting-edge landscape of artificial intelligence. Spearheaded by industry-recognized instructors Hitesh Choudhary and Piyush Garg, this program bridges the gap between theoretical AI concepts and real-world deployment. Students embark on a structured journey starting from fundamental concepts like tokenization, embeddings, and attention mechanisms, and progress rapidly toward building enterprise-grade, stateful multi-agent systems. The curriculum is heavily hands-on, covering critical modern tools such as Pydantic for structured data validation, LangChain for building complex LLM orchestrations, and LangGraph for designing advanced agentic workflows with custom nodes and edges. Learners also master the Model Context Protocol (MCP) to seamlessly connect AI agents to external data sources. On the deployment front, the course dives deep into running models locally via Ollama, utilizing Hugging Face, and containerizing application pipelines using Docker. By emphasizing Retrieval-Augmented Generation (RAG) alongside scalable Vector Databases, this course empowers software engineers, full-stack developers, and AI enthusiasts to construct, optimize, and deploy robust, production-ready AI solutions from scratch.