Learn how to build practical AI agents with Python using modern tools such as Ollama, LangGraph, Streamlit, Pydantic, ChromaDB, and Retrieval-Augmented Generation.
In this hands-on course, you will explore how agentic AI applications are designed, developed, and tested through real-world project examples. Instead of focusing only on basic chatbot interactions, this course introduces structured AI agent workflows that can use tools, retrieve information, follow instructions, and support human decision-making.
You will begin with the foundations of AI agent development, including how agents receive goals, manage prompts, produce structured outputs, and work with Python-based logic. You will build a personal AI assistant project and learn how to organize inputs, outputs, conversation history, and response formats.
Next, you will practice AI planning and task decomposition. You will learn how to break larger objectives into smaller steps, design reliable JSON outputs, and use Pydantic models to validate structured responses. These skills are useful for creating more predictable and maintainable Generative AI applications.
