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[100% Off] Mistral Ai Development: Ai With Mistral, Langchain &Amp; Ollama

Learn AI-powered document search, RAG, FastAPI, ChromaDB, embeddings, vector search, and Streamlit UI (AI)

Added on October 4, 2025 Development 3 min read

What you’ll 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.

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!

Description

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 Used

• Mistral 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.

• FastAPI – High-performance API framework for building AI-powered search endpoints.

• Streamlit – Create interactive AI search UIs for document-based queries.

• Python – Core language for AI development, API integration, and automation.

Why Take This Course?

• AI-Powered Search & Knowledge Retrieval – Build document-based AI assistants that provide accurate, AI-driven answers.

• Self-Hosted & Privacy-Focused AI – No OpenAI API costs or data privacy concerns—everything runs locally.

• Hands-On AI Development – Learn by building real-world AI projects with LangChain, Ollama, and Mistral AI.

• Deploy AI Apps with APIs & UI – Create FastAPI-powered AI services and user-friendly AI interfaces with Streamlit.

• Optimize AI Search Performance – Implement query optimization, better embeddings, and fast retrieval techniques.

Who Should Take This Course?

• AI Developers & ML Engineers wanting to build local AI-powered applications.

• Python Programmers & Software Engineers exploring self-hosted AI with Mistral & LangChain.

• Tech Entrepreneurs & Startups looking for affordable, cloud-free AI solutions.

• Cybersecurity Professionals & Privacy-Conscious Users needing local AI without data leaks.

• Data Scientists & Researchers working on AI-powered document search & knowledge retrieval.

• Students & AI Enthusiasts eager to learn practical AI implementation with real-world projects.

Course Outcome: Build Real-World AI Solutions

By the end of this course, you will have a fully functional AI-powered knowledge assistant capable of searching, retrieving, summarizing, and answering questions from documents—all while running completely offline.

Enroll now and start mastering Mistral AI, LangChain, and Ollama for AI-powered local applications.