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.