Objectives

• Understand the core principles of machine learning and their application in web environments. • Use browser-based ML libraries (e.g., TensorFlow.js, ml5.js) to build interactive and intelligent applications. • Deploy pre-trained models using ONNX.js and Hugging Face Inference APIs. • Build and expose custom ML models via Flask or FastAPI backends. • Compare cloud-based AI platforms (e.g., Google Teachable Machine, Azure ML Studio, IBM Watson) for different use cases. • Apply ethical, accessible, and responsible AI principles in web development. • Collaborate on and deploy real-world AI-powered web apps as final capstone projects.

Target Group

Frontend and backend web developers seeking to integrate AI/ML into their projects; Software engineers and programmers looking to expand into AI-enhanced applications; Technical staff in startups, fintech, government, or academia involved in web solutions; Educators and trainers who want to incorporate AI for learning and innovation; Digital product teams and creative technologists building interactive systems.