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New CSCS Graduate Certificate Curriculum
New CSCS Certificate Program Requirements
April 2000
The UM Center for the Study of Complex Systems (CSCS) is pleased to
announce a revised set of course requirements for the Rackham Graduate
Certificate in Complex Systems.
Note that students who are already in the CSCS Certificate Program may
elect to receive a certificate by fulfuling either the old or new requirements.
We encourage students who wish to enroll, or who would like additional
information, to contact Rick Riolo (rlriolo@umich.edu) or
Lori Coleman (cscs@umich.edu).
These new requirements reflect the experience we and our students
have gained after the first few years of the program. The goals of
the CSCS certificate program requirements include:
- Students should be familiar with a minimal set of concepts and terms,
some list of key people, models, and basic "complex systems phenomena."
Among other things, this will serve as part of a common "language" and
a basis for students to interact in meaningful ways.
- Students should have basic math and computer modeling skills, so that they:
- understand the uses and limits of these approaches;
- can implement their own simple models; and
- can understand at some minimal level 90% of the CSCS seminars.
- Students should have more advanced skills/knowledge is some area,
e.g., dynamical systems, computer modeling, or other approaches to
complex systems modeling, perhaps as applied to a particular domain.
- Overall, students should gain an appreciation for and skills at
applying a complex systems approach to understanding both their own
and other fields of study.
- Promote and maintain a sense of community among students.
Students must take five courses, including the Group A course, the Group C
course and at least one course from Group D. Within Group D students with
weaker mathematics backgrounds should take CSCS 510; students with stronger
math backgrounds should take CSCS 520 or 541. It is possible to replace
the Group D course with an equivalent advanced dynamical systems course or
in very special circumstances to replace the Group C course with an
equivalent course, but every student must take at least one of CSCS 510
or CSCS 530. The courses in Group B represent the minimal programming and
calculus background required for the courses in Groups C and D; we
anticipate that most students will not need to take these courses.
They do not count toward the five courses in the certificate program.
Group A
Group B
- CSCS xxx (Short course) Introduction to Writing C Programs
under Linux/Unix. This will be a new, 1 credit course.
- Math 413/SPP 513: Calculus for Social Science
Group C
Group D
Group E
Courses related to Complex Systems and approved for the certificate
program by the CSCS Director. The following is a representative list
of such courses as offered in the 1999-2000 academic year:
- EECS 598 -
Control of Motion in Animals and Machines
Instructor: Daniel E.Koditschek, EECS
- EECS 587:
Parallel Computing
Instructor: Quentin F. Stout, EECS
- IOE 474: Simulation of Complex Discrete Event Systems
Instructor: Steve Chick, IOE
- Physics 406:
Statistical Mechanics and Thermodynamics
Instructor : Franco Nori. Physics
- Epidemiology 802:
Compartmental Model Analysis of Epidemiologic Processes
Instructor: Jim Koopman, Epidemiology
- Psych 749:
Cognitive Functioning
Instructor: S. Kaplan (skap@umich.edu), Psychology; L. Fu (lfu@umich.edu), EECS
- Biochemistry 511 (1 credit)
Critical Discussions in Bioinformatics
Instructors: Dan Burns, U of M (course director); Maggie Johns, Parke-Davis
- Biochemistry 526 (2 credits)
Survey in Bioinformatics
Instructors: Philip Andrews, U of M (course director); Brian Moldover, Parke-Davis;
Denise Kirschner, U of M; Michael Sauvageau, U of M
- Biostatistics 866: Advanced Topics in Genetic Modeling
Instructors: Mike Boehnke, Biostatistics
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Honors 493: Complexity and Emergence
Instructor: John Holland, EECS & Psychology
-
EECS 547/SI 652:
Electronic Commerce
Instructor: Prof. Michael Wellman, EECS
-
Rackham 570: Spatio-Temporal
Complexity in Science and Engineering
Instructors: Prof. F. Nori, Physics; Prof. R. Ziff, Chemical Engineering
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Math 654:
Introduction to Fluid Dynamics
Instructor: Robert Krasny, Math
-
Math 526: Dicsrete State Stochastic Processes (Biological Applications)
Instructor: Dan Burns, Math
-
EECS 695/Psychology 640: Neural Models: Mechanisms of Learning
Instructor: S. Kaplan, Psychology; L. Fu, EECS
-
Psychology 643/EECS 643: Theory of Neural Computation
Instructor: Jun Zhang, Psychology
- NRE 639 Seminar - Does Space Matter in Natural Resources Research?
Instructor: Daniel G. Brown and Emily Silverman, Natural Resource and Environment
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