/networks-science-course

A course on Network Science, including network formation models, structural patterns, and dynamic processes.

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Network Science Course

Instructor: Carlos Castillo

These are materials for an undergraduate course on Network Science, and include two-hour lectures and two-hour practice sessions every week. They were developed for second year students of the bachelor degree on Mathematical Engineering on Data Science at Universitat Pompeu Fabra, Barcelona.

  • "It is a very interesting subject, and it seems very useful for data scientists." -- a student's evaluation from the 2021 edition
  • "This has been by far my favorite subject in the degree and the one in which I've learned the most." -- a student's evaluation from the 2020 edition.
  • "The most interesting subject so far ... the volume of work is quite a lot, but the topics are engaging." -- a student's evaluation from the 2019 edition.
  • "By far, the most interesting and fun subject of the trimester!" -- a student's evaluation from the 2018 edition.

Contents of this repository

🚧 These materials should not be considered final until the end of the course.

  • 📈 Theory: slides for the theory part.
  • 💻 Practicum: activities for practical sessions.
  • 📁 Datasets: to be used during practical sessions.
  • 📝 Exams from previous and current year.

Material specific to UPF students:

Acknowledgments

The course, particularly the first half, follows the book and course on complex networks by Albert-László Barabási.

I am thankful to the course's teaching assistants Fedor Vityugin (2020), Alexander Gomez (2018-2020) and Alexandra Matreata (2018) at UPF, and the feedback from Vicenç Gómez on an early version of this course.

Course materials are available under a Creative Commons license unless specified otherwise.