CDL COURSE ENTRY FORM


Author: Laura Wait/SUNY
Last modified by: Laura Wait/SUNY
Composed: 12/01/2014 04:01 PM
Curriculum Committee Approval Date: 11/06/2014
Modified: 04/26/2018
-----------------------------------------------------------------
Course Number: (prefix) SMT (number) 273244 ESC 2.0 Course number: MATH-3020 MATH-3020Graph Theory

Name: Graph Theory
Datatel Title: (30char) Graph Theory

Area Coordinator: Jennifer Blue Department Code: 10SM Team: SMT

Liberal Study? YES Level: UPPER Credits: 4 Prerequisite? YES
General Education Course? NO GenEd Approval Term/Year:

GenEd Area 1: Fully or Partially:
GenEd Area 2: Fully or Partially:



Pre-registration Information?
Course will be offered (for online course descriptions, proposed offerings for by term views and web views)
Summer		Course will be offered (for final term listings, online registration, online bookordering, web views)
Summer
First Term Offered: 2015SU (Required Format: YearTerm - i.e., 2005SP)
Last Term Offered in Print Version:
Title Changes:
AC Changes: EFFECTIVE 4/23/18 CHANGED BACK TO JEN BLUE 10SM. GAVE LYNAE 10AR. CATALOG UPDATED 4/26/18. LWAIT
EFFECTIVE SP1 2018 CHANGED FROM JEN BLUE TO LYNAE WARREN; SHE TOOK OVER THE 10SM DEPT CODE. CATALOG UPDATED 1/4/18. LWAIT
BK Number:

Description: What do transportation systems, social networks, the Web, powergrids, financial markets and many biological systems have in common? They are examples in which we seek to understand not only the entities which interact, but also the patterns of interaction between the entities. Graph theory and network science are rooted in Mathematics and Computer science. Topics covered in this course include: graphs as models, paths, cycles, directed graphs, trees, spanning trees, matchings (including stable matchings, the stable marriage problem and the medical school residency matching program), network flows, and graph coloring (including scheduling applications). Following this introduction to graph theory, students will explore theoretical network models, such as random graphs, small world models and scale-free networks, as well as networked datasets from social, infrastructure and information networks. In this context, we will explore topics such as the role of strong and weak ties, triadic closure, and centrality measures, as well as the fragility of networked systems and contagious process on networks of various topologies.

The primary audience for this course is students who wish to concentrate in Computer Science, Information Technology, Mathematics or Applied Mathematics. Students interested in various fields which have a connection to this branch of mathematics (such as cognitive science, data science, economics, computational sociology, mathematical biology) may also be interested in this course.

Prerequisites: Prior to enrolling in this course, students should be fluent in the foundations of mathematics and mathematical proof: logic, methods of proof (both inductive and deductive), sets, relations and functions. This knowledge may be obtained from a course such as Discrete Mathematics, for example.

Generic:



Major Course Area
Science Math & Technology		Minor Course Area
Math and Quantitative Studies		SLN Disciplines
Mathematics
Additional Course Requirements
 Undergrad Certificate Association:


0




Required Booknote:

Optional Booknote:


Archive Course:

genedcode for dpplanner:

genedfull area for dpplanner: