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 why it’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 documents

• Product recommendation engine using vector similarity

• Intelligent chatbot with memory stored in MongoDB

• RAG (Retrieval-Augmented Generation) pipelines

Everything 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