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Certificate of Graduate Study in Complex Systems


In a nutshell:

The Graduate Certificate is a five (5) course booster pack in Complex Systems and Data Science.


The Curious Platypus

Who it's for:

The graduate certificate can be earned by students as a complement for their graduate degrees across the University of Vermont, or as a stand-alone post-baccalaureate Graduate Certificate (online/or in person).



The Academic Background You'll Need


Prerequisites:

A Bachelor's degree and demonstrated proficiency in:

  • Calculus
  • Probability and statistics
  • Computer programming (Python, R, and Matlab will be most helpful)
Highly recommended (but not required):
  • Linear algebra
  • Note: Specific electives may have additional prerequisites


Once You've Joined the Team...
Time to Get with the Program


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, and
  • 0-2 B-list courses;
Or
  • 2 required core courses,
  • 1-3 A-list courses, and
  • 0-2 B-list courses.
Required Core Courses (3):
  • CSYS/MATH 6701: Principles of Complex Systems
  • CSYS/CS 6020: Modeling Complex Systems
  • CSYS/STAT/CS 5870: Data Science I - Experience

  • A-List Courses
    • CSYS 5766: Chaos, Fractals, and Dynamical Systems
    • CSYS/MATH 6713: Complex Networks
    • CSYS/CS 6520: Evolutionary Computation
    • CS/STAT 3560: Neural Computation
    • STAT 5530: Appl Time Series & Forecasting
    • CSYS/STAT/CEE 7980: Applied Geostatistics
    • CSYS/CEE 7920: Applied Artificial Neural Networks

  • B-List Courses
    • CSYS/STAT/CS 6870: Data Science II
    • MATH 5788: Mathematical Biology & Ecology
    • MATH 5230: Adv. Ordinary Differential Equations
    • ME 5410: Advanced Bioengineering Systems
    • EE 5320: Smart Grid
    • ME 6550: Multi-Scale Modeling
    • CSYS/EE 6990: Optimization in Engineering
    • PA 6080: Decision Making Models
    • PA 6170: Systems Analysis and Strategic Management
    • PA 6060: Policy Systems
    • PBIO 5940: Ecological Modeling
    • PBIO 5750: Global Change Ecology
    • PBIO 6940: Data Modeling for Envir Science
    • BIOL 3165: Evolution
    • CS 3060: Evolutionary Robotics
    • CS 3540: Machine Learning
    • CS 6540: Deep Learning
    • ENVS 4990: Envir. Modeling and Systems Thinking
    • CEE 6990A: Data Analytics for Water Resources

    Other courses may be approved by the Complex System and Data Science Curriculum Committee.

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