Deep Learning in Action: Prototyping, Deploying, and Scaling AI Models

This course focuses on how deep learning and other AI models are built, fine-tuned, explained, and deployed to create ethical, high-impact AI solutions across different data types (i.e., images, text, audio, time series, and video data). Through iterative, hands-on labs that trace the complete supervised-learning pipeline - data collection, data labelling, modeling, evaluation, and deployment - students gain the practical mastery to move fluently from raw data to production. Responsible design practices are woven in each step to surface social implications and align solutions with stakeholder values. This course also emphasizes human skills - communication, collaboration, critical thinking, and entrepreneurship - preparing teams to translate technical breakthroughs into viable products. Students complete capstone projects: scoping a real-world challenge, prototyping a multimodal model, and deploying it on cloud platforms. This course assumes foundational programming fluency.