Leverage your Node.js backend expertise to build production-ready AI systems. As a Node.js developer, you already understand the critical infrastructure that powers AI applications, async event loops, streaming data, API design, and serverless architectures. This path transforms those skills into AI engineering capabilities. You'll start by understanding how LLMs work under the hood, then immediately apply that knowledge using LangChain.js to build intelligent backends. Your experience with Express, Fastify, and serverless functions directly translates to creating AI APIs that handle streaming responses, manage conversation state, and orchestrate multiple AI providers. The path emphasizes RAG (Retrieval-Augmented Generation) backends, a natural fit for Node.js developers who already work with databases and search systems. You'll learn to build vector-powered APIs, implement semantic search, and create AI agents that can use tools and access external data. While JavaScript handles most AI engineering tasks, Python proficiency opens doors to specialized ML libraries and certain production deployments. You'll learn enough FastAPI to complement your Node.js skills without abandoning your backend expertise. By the end, you'll have a portfolio demonstrating AI API development, RAG systems, and full-stack AI applications. Timeline: 4-6 months of focused learning.
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build
Skills You'll Build