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: 09.01.2025 - 13.02.2025
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.
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
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Spring III
2025-2026 Spring III