MongoDB GenAI Developer
GenAI Skills
MongoDB’s document model simplifies the creation of a GenAI application, by storing your vectors alongside your data, you can add semantic search to your application using the same syntax you’re already familiar with. Here, you'll start by learning to perform a semantic search with Atlas Vector Search. After you become familiar with how vector search works, you'll use it to build a Retrieval Augmented Generation (RAG) application to create a custom chatbot. Upon completing each skill, you can validate your mastery through a short skill check to earn a Credly badge, which you can display on LinkedIn to highlight your expertise.
Milestone
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MongoDB GenAI Developer
Vector Search Fundamentals
RequiredSkill
| 1 HourLearn how to leverage MongoDB Atlas Vector Search to build intelligent, AI-powered search experiences for applications. Explore indexing, embeddings, and retrieval strategies.RAG with MongoDB
RequiredSkill
| 1 HourDiscover how to build Retrieval-Augmented Generation (RAG) applications with MongoDB. Learn to integrate vector search, optimize retrieval workflows, and enhance LLM-powered apps.AI Agents with MongoDB
RequiredSkill
| 1.25 HoursLearn how to build and deploy AI agents using MongoDB. Understand orchestration, data storage strategies, and how to integrate AI models with real-time databases.