Build AI Apps Locally with Mistral, LangChain & Ollama

Are you ready to build AI-powered applications with Mistral AI, LangChain, and Ollama? This course is designed to help you master local AI development by leveraging retrieval-augmented generation (RAG), document search, vector embeddings, and knowledge retrieval using FastAPI, ChromaDB, and Streamlit. You will learn how to process PDFs, DOCX, and TXT files, implement AI-driven search, and deploy a fully functional AI-powered assistant—all while running everything locally for maximum privacy and security.

In this course, you will set up and configure Mistral AI and Ollama for local AI-powered development. You will extract and process text from documents, converting it into embeddings with sentence-transformers and Hugging Face models. Efficiently store and retrieve vectorized documents using ChromaDB for AI search, while implementing Retrieval-Augmented Generation (RAG) to enhance your AI-powered question answering capabilities. You will also learn how to build an interactive AI chatbot interface using Streamlit for document-based search.

By the end of the course, you will have a fully functional AI-powered knowledge assistant capable of searching, retrieving, summarizing, and answering questions about documents—all while running completely offline. Enroll now and start mastering Mistral AI, LangChain, and Ollama for AI-powered local applications.

What you will learn:

• Set up and configure Mistral AI & Ollama locally for AI-powered applications.
• Extract and process text from PDFs, Word, and TXT files for AI search.
• Convert text into vector embeddings for efficient document retrieval.
• Implement AI-powered search using LangChain and ChromaDB.
• Develop a Retrieval-Augmented Generation (RAG) system for better AI answers.
• Build a FastAPI backend to process AI queries and document retrieval.
• Design an interactive UI using Streamlit for AI-powered knowledge retrieval.
• Integrate Mistral AI with LangChain to generate contextual responses.
• Optimize AI search performance for faster and more accurate results.
• Deploy and run a local AI-powered assistant for real-world use cases.

Course Content:

• Sections: 6
• Lectures: 19
• Duration: 2h 3m

Requirements:

• 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 for better performance).
• 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.
• Willingness to learn and experiment with AI-powered applications.
• Admin access to install necessary tools like FastAPI, Streamlit, and ChromaDB.
• A stable internet connection to download required models and dependencies.
• Curiosity and enthusiasm to build AI-powered search applications!

Who is it for?

• Anyone Curious About AI who wants to build practical AI applications without prior experience!
• Students & Learners eager to gain hands-on experience with AI-powered search tools.
• Cybersecurity & Privacy-Conscious Users who prefer local AI models over cloud solutions.
• Python Programmers looking to enhance their skills with AI frameworks like LangChain.
• Researchers & Knowledge Workers needing AI-based document search assistants.
• Tech Entrepreneurs & 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 & ML Engineers looking to integrate AI search into real-world projects.
• AI Enthusiasts & Developers who want to build local AI-powered applications.

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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