Building AI applications that actually work with your own documents used to require expensive cloud APIs and sending your data to third parties. This course teaches you how to build a private, local AI powered knowledge assistant using Mistral AI, LangChain, and Ollama. You will extract and process text from PDFs, Word, and TXT files, convert text into vector embeddings, implement AI powered search using LangChain and ChromaDB, build a Retrieval Augmented Generation (RAG) system, create a FastAPI backend, and design an interactive UI with Streamlit. Everything runs locally for privacy and zero API costs.

This Course Offers

• A complete local AI stack: Mistral AI, Ollama, LangChain, ChromaDB, FastAPI, and Streamlit.
• Document processing for PDF, DOCX, and TXT files.
• Vector embeddings and semantic search using sentence transformers.
• RAG implementation for contextual, accurate AI answers.
• A fully functional AI powered knowledge assistant for document based question answering.

Why We Love This Course

1. It focuses on local, privacy focused AI. No OpenAI API costs and no data privacy concerns.
2. Over 18,000 students have enrolled, and the course builds a real world application from start to finish.
3. The instructor covers the entire pipeline from document ingestion to embedding to retrieval to UI.
4. It is beginner friendly. Basic Python knowledge is recommended but not required, and no prior experience with Ollama, LangChain, or Mistral AI is needed.

The course last updated in February 2026. If you are an AI developer, Python programmer, tech entrepreneur, cybersecurity professional, data scientist, researcher, or student who wants to build practical, self hosted AI applications without relying on cloud APIs, this course gives you the hands on skills to build a private, powerful AI assistant.

• Anyone curious about AI who wants to build practical AI applications without prior experience.
• Students and learners eager to gain hands on experience with AI powered search tools.
• Cybersecurity and privacy conscious users who prefer local AI models over cloud solutions.
• Python programmers looking to enhance their skills with AI frameworks like LangChain.
• Researchers and knowledge workers needing AI based document search assistants.
• Tech entrepreneurs and startups exploring self hosted AI solutions.
• Backend engineers who want to implement AI powered APIs using FastAPI.
• Software developers interested in building AI driven document retrieval systems.
• Data scientists and ML engineers looking to integrate AI search into real world projects.
• AI enthusiasts and developers who want to build local AI powered applications.

• Basic Python knowledge is recommended but not required.
• Familiarity with APIs and HTTP requests is helpful but optional.
• A computer with at least 8GB RAM (16GB recommended).
• Windows, macOS, or Linux with Python 3.8+ installed.
• Basic understanding of AI concepts is a plus but not mandatory.
• No prior experience with Ollama, LangChain, or Mistral AI is needed.
• Admin access to install tools.
• A stable internet connection to download models and dependencies.

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