CS-E5740 - Complex Networks D, Lecture, 4.9.2024-9.12.2024

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 with fundamentals of complex network theory, together with skills for applying this knowledge in to practical network analysis.

Credits: 5

Schedule: 04.09.2024 - 09.12.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Jari Saramäki, 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:

    Introduction to complex networks, fundamentals and basic concepts. Fundamental models: random networks, small-world networks, and scale-free networks. Network measures and analysis. Error and attack tolerance of networks, percolation, thresholds for epidemic spreading. Weighted networks. Social networks. Network inference. Clustering and communities. Multilayer and temporal networks.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Grades are given on the basis of weekly exercises and project work, there is no exam. Exercises and project work require Python programming, but you do not need to be familiar with Python beforehand, as long as you have some programming skills.

Workload

  • valid for whole curriculum period:

    9 lectures + 8 sets of weekly exercises + project work. Attending lectures or exercises sessions is not mandatory, but returning completed weekly exercise sets is.

DETAILS

Study Material

  • valid for whole curriculum period:

    Lecture slides/video streams and references therein.

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Autumn I - II
    2025-2026 Autumn I - II

    Registration:

    Students of Life Science Technologies have priority

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof