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Mathematical Modeling: Networks
Cursusdoel
- Understand and describe the importance of network theory, both in general and in a particular field of their interest.
- Use mathematical concepts to characterize and analyze network structures in a variety of real-world settings such as infrastructure networks, social networks, and networks of data.
- Apply concepts and techniques of linear algebra and graph theory in this setting.
- Explain how to build and analyze concrete mathematical models, e.g. of financial crises or the spread of diseases.
- Conduct a small research project based on current academic literature in the area of the course, and present findings orally and in writing.
In this course, the final course grade is based on five elements: active presentation, two written exams, homework and a paper presentation and report.
1. Written in-class exam 1: this tests your knowledge and ability to analyze networks and algorithms and their basic properties. The theory is covered in the first 6 weeks of the course.
2. Written in-class exam 2: this tests your knowledge and ability to analyze more general networks such as random networks and algorithms and their basic properties. The theory is covered in weeks 9-14 of the course.
3. Active participation: this tests the participation during the lectures including online short tests in the beginning of every lecture.
4. Homework: this element tests your ability to apply theory to exercises and write out a solution.
5. Paper presentation: in this element you can demonstrate your ability to perform a small research project in written paper and presentation applying the theory which you learned in class.
Vakinhoudelijk
The interdisciplinary study of networks is recently receiving much attention. It is revealing unexpected connections between otherwise disparate fields such as sociology, ecology, economics, cognitive neuroscience, and computer science. Network thinking provides new ways to understand our strongly connected world. This approach has generated new tools for the analysis and understanding of complex systems in both the social and natural world.
The course will discuss how to describe and quantify networks, provide means to analyze network data (using among others graph theory) and explain how to build and analyze concrete mathematical models, e.g. of the spread of diseases or of financial crises.
In addition to the contact hours, each student is expected to work nine hours a week on the course. This time should be devoted to: reviewing the material of the preceding and for the following lecture; finishing and preparing exercises (some to be handed in); reading research articles, writing a final essay, preparing for a presentation.
UCSCIMAT22 does not give access to UCSCIMAT31. Students wanting to complete a track in mathematical modeling are advised to do so with a suitable level-3 off-campus course.
For students wanting to complete a track in applied mathematics there are interesting level-3 Bachelor courses in social science (economic geography, sociology) and humanities (artificial intelligence, logic, linguistics) and also in science (e.g. in theoretical biology).
- GEO3-3805, ECON-Organisational Networks, Matté Hartog (economic geography)
- 200700372, Social Networks (ECO). Dr. Gerard Mollenhorst (sociology)
- 200800018, MK: Social networks. Dr. Gerard Mollenhorst
- B-B3COMB10, Computational Biology, Prof. dr. Paulien Hogeweg
- KI3V12013, Logical Complexity, Dr. R. Iemhof
Master courses (no easy access but to indicate importance of networks):
- WBMV13005, Logic and Computation [Prof. Vincent van Oostrom]
- BMB508112, Bioinformatics in neuroscience [Prof. dr. R. Adan]
- WISM484 Introduction to complex systems (Prof. Dr. Jason Frank)
Werkvormen
Toetsing
Active participation
Verplicht | Weging 10% | ECTS 0,75
Homework assignments
Verplicht | Weging 20% | ECTS 1,5
*midterm FEEDBACK*
Niet verplicht
Written exam 1
Verplicht | Weging 25% | ECTS 1,88
Written exam 2
Verplicht | Weging 25% | ECTS 1,88
Final paper & presentation
Verplicht | Weging 20% | ECTS 1,5
Ingangseisen en voorkennis
Ingangseisen
Er moet voldaan zijn aan de cursussen:
Voorkennis
Alternatively, UCSCIMAT14 can also serve as a prerequisite with instructor's approval.
Voertalen
- Engels
Competenties
-
Interdisciplinariteit
-
Presenteren
Tentamens
Er is geen tentamenrooster beschikbaar voor deze cursus
Verplicht materiaal
Materiaal | Omschrijving |
---|---|
BOEK | Mark Newman, Networks, Oxford University Press (2018), ISBN-10: 0198805098 |
Aanbevolen materiaal
Er is geen informatie over de aanbevolen literatuur bekend
Coördinator
dr. A.E.M. van de Ven | A.E.M.vandeVen@uu.nl |
Docenten
dr. W.M. Ruszel | W.M.Ruszel@uu.nl |
Inschrijving
Inschrijving niet via OSIRIS
Permanente link naar de cursuspagina