Build Local AI Apps with Ollama, Python, and Streamlit

About this course

Build powerful, private, and practical AI applications directly on your own computer with Ollama, Python, and Streamlit.

This hands-on course teaches you how to create complete local AI apps without depending on paid AI APIs or sending sensitive information to external cloud services. You will learn how to run large language models locally, connect them to Python, design effective prompts, build interactive user interfaces, and transform simple ideas into useful AI applications.

The course begins with the foundations of local artificial intelligence. You will install Ollama, download and manage local models, adjust model parameters, write system instructions, and connect your models to Python applications. You will then use Streamlit to create clean, browser-based interfaces that make your AI projects easy to use and demonstrate.

As you progress, you will build conversational applications with chat history, memory, customizable personas, session state, conversation exports, and reset controls. You will also learn how to process PDF and text documents, clean and chunk content, generate local embeddings, store vectors in ChromaDB, and perform semantic search across private knowledge.

Next, you will build complete Retrieval-Augmented Generation, or RAG, applications. You will retrieve relevant document sections, construct grounded prompts, generate answers with sources and page references, reduce hallucinations, and handle questions that are not supported by the available documents.

The course also covers structured AI outputs, reusable prompt templates, JSON generation, summarization, flashcards, quizzes, progress tracking, and learning applications. You will then move into tool-using AI, where models can call Python functions, orga

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