Mistral AI Development: AI with Mistral, LangChain & Ollama

About this course

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.

What You’ll Learn in This Course?

Set up and configure Mistral AI and Ollama for local AI-powered development.

Extract and process text from documents using PDF, DOCX, and TXT file parsing.

Convert text into embeddings with sentence-transformers and Hugging Face models.

Store and retrieve vectorized documents efficiently using ChromaDB for AI search.

Implement Retrieval-Augmented Generation (RAG) to enhance AI-powered question answering.

Develop AI-driven APIs with FastAPI for seamless AI query handling.

Build an interactive AI chatbot interface using Streamlit for document-based search.

Optimize local AI performance for faster search and response times.

Enhance AI search accuracy using advanced embeddings and query expansion techniques.

Deploy and run a self-hosted AI assistant for private, cloud-free AI-powered applications.

Key Technologies & Tools UsedMistral AI – A powerful open-source LLM for local AI applications.

Ollama – Run AI models locally without relying on cloud APIs.

LangChain – Framework for retrieval-based AI applications and RAG implementation.

ChromaDB – Vector database for storing embeddings and improving AI-powered search.

Sentence-Transformers – Embedding models for better text retrieval and semantic search.</

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