Covers the general logistics, course rationale, prerequisites, organization, credits, workload, grading, and course content, including swarm intelligence, foraging strategies, and collective phenomena.
Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.
Explores inverse design optimization in geometric computing, covering topics such as deployable structures, material-aware design, and programmed materials.
