COMP8880 Computational Methods for Network Science

Not offered in 20266 units8000-level

Computational Methods for Network Science covers the essentials of using computational approaches to pose and answer social science research problems. In doing so it also covers a selected set of network algorithms in depth. This includes random graph models, homophily and friendship paradox, influence and contagion in networks, markets and network games, network resilence. Furthermore, it also teaches students about the ethics of doing data-driven social science research. The course equips the students with in-depth knowledge and hands-on experience in working with network data to study social processes at both the individual and aggregate levels. Graduates will be equipped with the technical, theoretical and conceptual skills and knowledge to start a budding career in this field of research.

2024S1
2025S1
2026not offered
2027not offered

Prerequisites in 2026

Read automatically from the handbook's wording

One of

COMP6670Introduction to Machine Learning
All of
- One of
  - COMP6710Structured Programming
  - COMP6730Programming for Scientists
  - COMP7230Introduction to Programming for Data Scientists
- One of
  - COMP8410Data Mining
  - COMP8910Data Mining
- STAT6039Principles of Mathematical Statistics

Incompatible with COMP4880, COMP8980: you can't count both.

The handbook's wording, and when it changed

2024–2026
To enrol in this course you must have completed COMP6670 ; OR (6 units of either COMP6710 or COMP6730 or COMP7230 ) and (either COMP8410 or COMP8910 ) and STAT6039 . Incompatible with COMP4880 and COMP8980 .
2027
To enrol in this course you must have completed COMP6670 . Incompatible with COMP4880 .

What it leads to in 2026

No course names COMP8880 in its 2026 prerequisites.

COMP8880 in the 2026 handbook on Programs and Courses