Lilly Tech Systems
JavaScript/TypeScript for AI
Build AI-powered web applications — run machine learning in the browser, integrate LLMs with LangChain.js, and deploy real-time AI in frontend and Node.js apps.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Why JavaScript for AI, the browser as an ML platform, Node.js AI ecosystem, and TypeScript advantages.
2. TensorFlow.js
Train and run ML models in the browser, transfer learning, WebGL acceleration, and model conversion.
3. Transformers.js
Run Hugging Face transformer models client-side: text generation, sentiment analysis, image classification.
4. ONNX Runtime
Run ONNX models in the browser and Node.js with ONNX Runtime Web, model optimization, and WebGPU.
5. LangChain.js
Build LLM applications with chains, agents, RAG, memory, Vercel AI SDK, and streaming responses.
6. Best Practices
Web Workers for inference, performance optimization, privacy advantages, deployment, and real-time AI UX.
What You'll Learn
By the end of this course, you'll be able to:
Run ML in the Browser
Execute machine learning models entirely client-side with no server, no API calls, and complete user privacy.
Build AI-Powered Apps
Create chatbots, image classifiers, sentiment analyzers, and text generators using JavaScript frameworks.
Integrate LLMs
Connect to OpenAI, Anthropic, and open-source models using LangChain.js and Vercel AI SDK.
Optimize Performance
Use Web Workers, WebGL, WebGPU, and model quantization for fast, responsive AI experiences.