Applied AI and LLM Development: Build 100 Projects in Python

The demand for AI developers is growing rapidly, but true mastery comes from writing code and building systems, not just reading theory. This course offers a direct, highly practical path to understanding and deploying artificial intelligence technologies on your own machine. You will transition from an AI enthusiast to a capable developer by building a massive portfolio of practical projects. Through clear, step-by-step written explanations and code walkthroughs, you will learn to build, run, and orchestrate intelligent applications locally, giving you complete control over data privacy and system performance. What you'll learn: - Understand foundational AI concepts, modern Python environments, and prompt engineering principles. - Build custom applications using local LLMs with Ollama to ensure complete data privacy. - Develop interactive AI interfaces using Streamlit for seamless user experiences. - Implement retrieval-augmented generation (RAG) using vector databases like ChromaDB for custom knowledge retrieval. - Create autonomous multi-agent systems using LangChain and advanced orchestration frameworks. - Deploy and evaluate local AI applications using modern development workflows and performance best practices. The course starts with essential terminology and setting up your local Python environment before progressing through increasingly sophisticated projects. You will work through structured written guides that explain the architecture, logic, and code behind chatbots, search tools, and autonomous agents. This course is designed for beginners, self-taught programmers, and developers looking to pivot into AI. It requires only basic Python knowledge and no prior AI experience. Start building your AI portfolio today and master the tools shaping the future of software.