LEARNING OUTCOMES
This course is intended to be taken after CS-E5740 Complex Networks; it will deepen the students knowledge on network analysis techniques and dealing with empirical network data, including network visualization, Python programming, and statistical analysis. Students will also learn how to conduct team research and how to present their findings to their peers.
Credits: 5
Schedule: 28.02.2025 - 09.05.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jari Saramäki
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:
Project work in groups. Hands-on analysis of network-related data.
Assessment Methods and Criteria
valid for whole curriculum period:
Pass/fail. Pass = active participation in projects as member of a group, presence at project meetings and (oral) presentation of project results in these meetings.
Workload
valid for whole curriculum period:
Contact teaching and group work (6 x 4 h), independent studying (research articles), independent group work. Mandatory attendance.
DETAILS
Study Material
valid for whole curriculum period:
The students will be provided with articles and materials related to their group work topics.
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 IV - V
2025-2026 Spring IV - VRegistration:
Students of Life Science Technologies have priority.