Complex Systems Program

Graduate Certificates

Complex Systems offers graduate certificates in two specialty areas: Computational Intelligence and Computer Modeling & Simulation. In order to earn a graduate certificate, a student must:

  • complete 15 credit hours of courses in the specialty area;
  • earn a GPA of 3.25 for these courses; and
  • complete the online Application for Graduation

How to Apply

Current MS/PhD Students

Students admitted to the master’s or doctoral program need not apply separately for admission to a graduate certificate. To add the certificate to their master’s or doctoral program, students must submit the GO-19M or GO-19D form to The Graduate School at least one term before they apply for completion of the certificate.

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New Students

Students not admitted to the doctoral or master’s program must submit to Complex Systems: (1) a completed Application to Graduate Program form, and (2) official or unofficial copies of academic transcripts from an institution. The admissions committee will recommend the student’s admission if his or her academic transcript shows a completed undergraduate degree with a GPA of 2.75 or higher.

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Computational Intelligence

The graduate certificate in Computational Intelligence encompasses neural networks, evolutionary computing, fuzzy set theory, and artificial intelligence. Typical application areas include pattern recognition, data-mining, control, signal processing, and non-linear optimization.

Required Course

  • SySc 575 AI: Neural Networks I (4 credits)

Electives (11 credits chosen from the following courses):

  • CS 541 Artificial Intelligence (3 credits)
  • CS 545 Machine Learning (3 credits)
  • CS 546 Advanced Topics in Machine Learning (3 credits)
  • CS 570 Machine Learning Seminar (1 credit)
  • ECE 510 Topics: Mathematical Foundations of Machine Learning (4 credits)
  • SySc 551 Discrete Multivariate Modeling (4 credits)
  • SySc 557 Artificial Life (4 credits)

15 credits total.

Computer Modeling & Simulation

The graduate certificate in Computer Modeling & Simulation encompasses linear systems theory, discrete, agent-based, and continuous system simulation, and statistical modeling of structure. Typical application areas include process engineering, policy evaluation, data analysis & interpretation, and the study of feedback dynamics in complex systems.

Required Course

  • SySc 514 System Dynamics (4 credits)

At least one of the following two courses:

  • SySc 525 Agent Based Simulation (4 credits)
  • SySc 527 Discrete System Simulation (4 credits)

Electives (one of the following courses if all three of the above courses are taken; otherwise, two of the following courses):

  • CS 545 Machine Learning (3 credits)
  • Psy 523 Structural Equation Modeling (4 credits)
  • SySc 535 Modeling & Simulation with R and Python (4 credits)
  • SySc 540 Introduction to Network Science (4 credits)
  • SySc 551 Discrete Multivariate Modeling (4 credits)

15-16 credits total.