CS-E5745 - Mathematical Methods for Network Science D, Lecture, 12.1.2023-16.2.2023

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

This course will provide students an overview on mathematical topics and tools in network science. The students will develop skills in doing pen-and-paper calculations and an understanding of analytical methods that are common in network science.

Credits: 5

Schedule: 12.01.2023 - 16.02.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Mikko Kivelä

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Mathematical methods and their use in networks science. Topics are mostly related to large random graphs and include  common approximations and assumptions  in network science, network models,  component size distributions, percolation,  branching processes, excess degree distributions, probability generating functions, master  equations, rate equations, growing network models, processes on networks, exponential  random graphs, and stochastic block  models. The project can be on a recent research topic.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Grades (1-5) are given on the basis of weekly mandatory exercises and project work, there is no exam.

Workload

  • valid for whole curriculum period:

    The course has lectures and two exercise sessions weekly. One of the weekly exercise sessions has mandatory participance. The workload of 135 hours (=5 ECTS) is divided into 24 hours of contact studies in exercise sessions, 12 hours of lectures, and 99 hours of self-study (including exercises, reading the course book, and reviewing lecture materials) and reflection.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring III
    2023-2024 Spring III

    Enrollment :

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

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