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COURSE DESCRIPTION AND APPLICATION INFORMATION

Course Name Code Semester T+A+L (hour/week) Type (C / O) Local Credit ECTS
Complex Networks and Their Applications CSE 510 Spring 03+00+00 Elective 3 7.5
Academic Unit:
Mode of Delivery: Face to face
Prerequisites: Calculus, Linear algebra, Probability, Ordinary Differential Equations, Python Programming Language.
Language of Instruction: English
Level of Course Unit: Graduate
Course Coordinator: DENİZ EROĞLU
Course Lecturer(s): DENİZ EROĞLU
Course Objectives: Goal: The emphasis throughout the course is on internalizing basic concepts of network theory and sharpening problem-solving skills. Student Learning Outcomes: Complex networks analysis. Understand mathematics of complex networks, statistical properties of networks, mathematical models to generate networks and processes on networks. Identify and solve network problems in applied sciences.
Course Contents: mathematics of networks, algebraic concepts in network theory, spectra of the network representing matrices, degree distribution, clustering coefficients, centrality measures, random network models, real-world networks, processes on networks
Learning Outcomes of the Course Unit (LO):
  • 1- Complex networks analysis
  • 2- Understand mathematics of complex networks
  • 3- statistical properties of networks, mathematical models to generate networks and processes on networks
  • 4- Identify and solve network problems in applied sciences.
Planned Learning Activities and Teaching Methods: The course is designed to benefit students of complex systems to learn basic network theory concepts. The course provides an eminently valuable introduction to the study of network theory, spectral properties of networks, random network models, processes on networks and their real-world applications. The material covered in this subject is intended to provide you with the mathematical tools and understanding of complex networks.


WEEKLY SUBJECTS AND RELATED PREPARATIONS

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REQUIRED AND RECOMMENDED READING

Textbooks:
- A First Course in Network Theory by E. Estrada and P.A. Knight [2015]
- Complex Graphs and Networks by F. Chung and L. Lu [2004]


OTHER COURSE RESOURCES

Lecture notes will be provided.


ASSESSMENT METHODS AND CRITERIA

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Total: 0 0


WORKLOAD

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THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES (LO) AND PROGRAM QUALIFICATIONS (PQ)

# PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10
LO1                    
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LO4