24-679 Special Topics: Designing and Prototyping AI Systems
12 units, Carnegie Mellon University
This course introduces theory, methods, and techniques for designing and prototyping AI systems, with a focus on building and experimenting with interactive computational artifacts. Students gain hands-on experience with modern Python-based AI/ML libraries and workflows, including automated machine learning, low-code interfaces for rapid prototyping, and the use of powerful pre-trained models for intelligent workflows and agents. The course begins by familiarizing students with contemporary software engineering and development practices, including how these workflows are increasingly supported and transformed by AI tools. Next, students learn how to collect and curate data, train, fine-tune, and apply AI models, and rapidly prototype interactive user experiences around them. Finally, students consider the intersection of AI with design, exploring human-AI teaming, human-computer interaction (HCI), and broader social and ethical dimensions of deploying AI systems in practice. Several projects, both team-based and individual, challenge students to design and prototype an AI/ML system that responds to specific stakeholder needs, demonstrating both intelligence and meaningful interaction. Students are also assessed through a series of structured homework assignments. An undergraduate level understanding of statistics, numerical methods, and programming in Python is expected.
Prerequisites: none listed
Offered: Fall 2026, Fall 2025
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