Mongodb + Ai: Build Intelligent Apps With Vector Search Llms
Published 12/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 19m | Size: 450 MB

Build AI-powered apps using MongoDB, vector search, embeddings, and LLM integration-step-by-step, beginner friendly.
What you'll learn
Learn to store, index, and query vector embeddings in MongoDB for intelligent AI-driven search.
Build full-stack AI apps using LLMs, vector search, and real-time data pipelines with MongoDB Atlas
Implement RAG workflows to boost LLM accuracy, reduce hallucinations, and deliver context-aware results.
Deploy scalable, production-ready AI features with indexing, performance tuning, and secure APIs.
Requirements
Students should have basic computer skills, beginner-level programming knowledge, and a willingness to learn MongoDB and AI concepts.
Description
Welcome to MongoDB + AI: Build Intelligent Apps with Vector Search & LLMs, a hands-on course designed for developers who want to combine modern NoSQL databases with cutting-edge artificial intelligence. This course takes you from MongoDB fundamentals all the way to building real, production-ready AI-powered applications using embeddings, vector search, and Large Language Models (LLMs).You'll begin with a solid foundation in MongoDB-documents, collections, indexes, schema design, and performance basics. Once your core skills are ready, we transition into the world of AI-driven search and retrieval, where you'll learn how embeddings work, how vector similarity search differs from keyword search, and w***t's essential for AI apps.Next, we dive deep into MongoDB Atlas Vector Search, where you'll implement semantic search, re-ranking pipelines, hybrid search, metadata filtering, and more. You'll work with popular embedding models and learn how to store, index, and query high-dimensional vectors efficiently.From there, we integrate MongoDB with LLMs like GPT, Claude, and open-source models, building projects such as:AI-powered Q&A bot using your own documentsProduct recommendation engine using vector similarityIntelligent chatbot with memory stored in MongoDBRAG (Retrieval-Augmented Generation) pipelinesEverything is taught using clear explanations, real-world examples, and step-by-step coding sessions. By the end of this course, you'll be able to build end-to-end AI features that are smart, scalable, and production-ready.If you want to upgrade your AI development skills and build intelligent applications powered by MongoDB and modern LLM technology-this course is made for you.
Who this course is for
For beginners, developers, and AI learners who want to build real-world intelligent apps using MongoDB and LLMs.
Ideal for students and developers eager to integrate vector search and AI features into modern applications