Mathematics

Graph Theory(MAT332)

Course Code Course Name Semester Theory Practice Lab Credit ECTS
MAT332 Graph Theory 6 5 0 0 3 5
Prerequisites
Admission Requirements
Language of Instruction
Course Type Elective
Course Level Bachelor Degree
Course Instructor(s) Serap GÜRER serapgurer@gmail.com (Email)
Assistant
Objective -This course aims to introduce the basic concepts, topics and results of Modern Graph Theory with a target of techniques that are applicable in especially social sciences.
Content Basic graph theoretical concepts: paths and cycles, connectivity, trees, spanning subgraphs, bipartite graphs, Hamiltonian and Euler cycles.
Algorithms for shortest path and spanning trees.
Matching theory.
Planar graphs.
Colouring.
Flows in networks, the max-flow min-cut theorem.
Erdös-Rényi random graphs.
Szemerédi´s regularity lemma.
Infinite graphs.
Applications in computer science and social sciences.
Course Learning Outcomes On completion of the course, the student should be able to:

1)know some important classes of graph theoretic problems;
2) formulate and prove central theorems about trees, matching, connectivity, colouring and planar graphs;
3) describe and apply some basic algorithms for graphs;
4) use graph theory as a modelling tool.
Teaching and Learning Methods
References Graph theory, Diestel, Reinhard., 4th ed.: Heidelberg: Springer, 2010.
Graph Theory with Applications, Bondy.and Murty, North-Holland, 1979
Graph Based Natural Language Processing and Information Retrieval / Rada Mihalcea, Dragomir Radev, Cambridge University Press, 2011.
Discrete Mathematics, An Open Introduction, Oscar Levin, at
http://discretetext.oscarlevin.com/
Proof Techniques in Graph Theory, Harary, F. , Academic Press, New York, 1969.
New Directions in the Theory of Graphs, Harary, F., Academic Press, New York, 1973.
Print the course contents
Theory Topics
Week Weekly Contents
1 Fundamental Concepts of Graph Theory
2 Paths and cycles
3 Trees
4 Basics of matching theory
5 Algorithms for the shortest path
6 Algorithms for spanning trees
7 Midterm Exam
8 Planar Graphs and Coloring
9 Planar Graphs and Coloring
10 Large Graphs and Clustering
11 Large Graphs and Clustering
12 Presentations of projets
13 Applied Graph Theory and Modeling
14 Applied Graph Theory and Modeling
Practice Topics
Week Weekly Contents
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 3 60
Contribution of final exam to overall grade 1 40
Toplam 4 100
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 1 10
Midterm Examinations (including preparation) 1 30
Project 1 20
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 3 60
No Program Learning Outcomes Contribution
1 2 3 4 5
1 understands principles of deductive reasoning; has experience to verify well-foundedness and exactness of mathematical statements in systematic ways; X
2 can properly state and use concepts and results of major mathematical interest; X
3 masters current computational techniques and algorithms; has a good ability in their use; can identify relevant tools, among those one has learned, suitable to solve a problem and is able to judge whether or not one is in possession of these tools; X
4 is able to express one’s mathematical ideas in an organised way both in written and oral forms; X
5 understands relations connecting substantial concepts and results; can switch from one viewpoint to another on mathematical objects (pictures, formulae, precise statements, heuristic trials, list of examples,...); X
6 has followed individually a guided learning strategy; has pursued steps toward the resolution of unfamiliar problems; X
7 has a theoretical and practical knowledge in computer science well adapted for learning a programming language; X
8 has investigated the relevance of modeling and using mathematical tools in natural sciences and in the professional life; is conscious about historical development of mathematical notions; X
9 has followed introduction to some mathematical or non-mathematical disciplines after one’s proper choice; had experience to learn selected subjects according to one’s proper arrangement; X
10 masters French language as well as other foreign languages, to a level sufficient to study or work abroad. X
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 14 2 28
Assignments 6 4 24
Presentation 1 1 1
Midterm Examinations (including preparation) 1 8 8
Project 1 8 8
Laboratory 0 0 0
Other Applications 0 0 0
Final Examinations (including preparation) 1 12 12
Quiz 0 0 0
Term Paper/ Project 0 0 0
Portfolio Study 0 0 0
Reports 0 0 0
Learning Diary 0 0 0
Thesis/ Project 0 0 0
Seminar 0 0 0
Other 0 0 0
Total Workload 123
Total Workload / 25 4.92
Credits ECTS 5
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