The Certificate requirement is 5 courses (15 credits), with a minimum GPA of 3.0 in all 5 courses.
Structure:
3 required core courses; 1-2 A-list courses; 0-2 B-list courses
Or
2 required core courses; 1-3 A-list courses; 0-2 B-list courses
Required Core Courses (3)
CSYS/MATH 300: Principles of Complex Systems
CSYS/CS 302: Modeling Complex Systems
STAT/CS 287: QR: Data Science I
A-List Courses (Select 1 to 2)
CSYS/MATH 266: Chaos, Fractals, and Dynamical Systems
CSYS/MATH 303: Complex Networks
CSYS/BIOL/CS 352: Evolutionary Computation
CSYS/CS 256: Neural Computation
CSYS/STAT 253: Appl Time Series & Forecasting
CSYS/STAT/CE 369: Applied Geostatistics
CSYS/CE 359: Applied Artificial Neural Networks
B-List Courses (Select 0 to 2)
STAT 387: Data Science II
CSYS/MATH 268: Mathematical Biology & Ecology
MATH 330: Adv. Ordinary Differential Equations
CSYS/CE 295: Reliability of Engineering Systems
CSYS/ME 295: Systems and Synthetic Biology
CSYS/ME 312: Advanced Bioengineering Systems
EE 217: Smart Grid
CSYS/ME: Multi-Scale Modeling
CSYS/EE 395: Optimization in Engineering
PA 308: Decision Making Models
PA 317: Systems Analysis and Strategic Management
PA 306: Policy Systems
BIOL 271: Evolution
CSYS/PBIO 295: Ecological & Environmental Modeling
CS 206: Evolutionary Robotics
CS 254 Machine Learning
CS 354 Deep Learning
ENVS 295: Envir. Modeling and Systems Thinking
NR 385: Energy Systems Transitions
PHYS 323: Phase Transitions and Critical Phenomena
Other courses may be approved by the Complex System and Data Science Curriculum Committee.