Rapid AI Systems: From Prototype to Production - 705.704

This advanced, project-driven course prepares students to become production-ready AI engineers by focusing on the real-world challenges of designing, building, and deploying end-to-end AI systems at startup speed. Rather than emphasizing theory or isolated tools, the course develops an engineering mindset centered on system architecture, practical decision-making, and cloud-native development practices. Students work both independently and collaboratively to architect, implement, and deploy a complete, portfolio-ready AI system in the cloud, using current, state-of-the-art technologies. Key topics include the design of optimized data pipelines for handling real-world datasets; the adaptation and integration of pre-trained machine learning models into scalable, high-performance ensembles; and the development of elastic, stateless system architectures leveraging message queuing, NoSQL databases, and managed cloud services. The course also covers modern deployment practices, including containerization, orchestration, and continuous integration/continuous deployment (CI/CD), along with production monitoring strategies to ensure observability, reliability, and high availability. Generative AI tools are actively incorporated and encouraged throughout the development process.The course is offered in a hybrid-live format. Attendance is required for four hands-on, lab-focused sessions. An additional four live sessions are optional and designed to keep course content aligned with rapidly evolving industry practices; all sessions are recorded and available for later viewing.