Explores challenges and solutions in resource-aware machine learning for IoT devices, including power analysis, classification, and dataset evaluation.
Covers the general logistics, course rationale, prerequisites, organization, credits, workload, grading, and course content, including swarm intelligence, foraging strategies, and collective phenomena.
Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.
Explores the physics of genetic and cellular systems, focusing on fragility, negative feedback loops, and sensory motor networks in the C. elegans brain.