CDS course discussion, Apr 2014

CMS course requirements

Core requirements: 7 common courses taken by all CMS students (first year) Depth requirement: 3 courses in a given area (e.g., Feedback & control, Inference & statistics, Information systems, Networked systems, Optimization, Uncertainty quantification) Breadth requirement: 3 courses from mathematics, science, engineering, or economics

Track	Fall	Winter	Spring
Core	ACM 104. Linear algebra and applied operator theory ACM/EE 116. Introduction to stochastic processes and modeling ACM 113. Mathematical optimization network	CS/EE 144. Networks: Structure and economics ACM/EE 218. Statistical inference and learning signal	ACM 126. Mathematical signal processing CS 139. Theory of algorithms
Feedback and control	CDS 110a - Analysis and design of feedback systems	CDS 110b - Control system design CDS 140a - Dynamical systems CDS 212 - Feedback control theory	CDS 140b - Dynamical systems (alt years) CDS 213 - Robust control CDS 270 - Advanced topics (nonlinear, adaptive, system ID)

Additional CMS courses

Track	Fall	Winter	Spring
Mathematics	CDS 201 - Linear Algebra & Applied Operator Theory Jointly offered with ACM 104/AM 125a Vector spaces, including Banach and Hilbert spaces Linear operators, dual spaces, decompositions ~35 students, multiple options ACM 113 - Introduction to Optimization Convex analysis Linear programming/duality
Stochastic systems	Introduction to Stochastic Processes and Modeling ACM/EE 116 (Hassibi, Owhadi, Tropp) Probability spaces, conditional probability, random processes ~100 students/year from across the Institute	Markov Chains, Discrete Stochastic Processes and Applications ACM 216 (Owhadi, Tropp)	Stochastic Inference ACM 218 (Chandrasekaran) CDS 150 (Beck)
Dynamical Systems	CDS 140a -
Robust Control	Modern Control Theory CDS 212 (Doyle, Low, Murray) Dynamics and stability in discrete and continuous time Uncertainty and robustness Fundamental limits: Bode, Shannon, Bode/Shannon	Algorithmic Game Theory CS/Ec 241