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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.

  • "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:

This course will be delivered face to face in 2021, although it was adapted for online learning in 2020. The main changes were that theory lessons are divided into smaller modules, there is only one midterm exam instead of two, no two-people assignments are requested, and individual practices are a little bit longer but more time is given to complete them.

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.

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