Instructor: Michele Starnini.

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.

Quotes from student evaluations (year)

• "I liked the most the algorithms from the last topics (PageRank, community finding, and spectral graph clustering)." (2023)
• "Despite being many practices and even some dense ones, I appreciated them because it helped you to consolidate the theory concepts." (2022)
• "It is a very interesting subject, and it seems very useful for data scientists." (2021)
• "This has been by far my favorite subject in the degree and the one in which I've learned the most." (2020)
• "The most interesting subject so far ... the volume of work is quite a lot, but the topics are engaging." (2019)
• "By far, the most interesting and fun subject of the trimester!" (2018)

🚧 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:

• 📜 Course presentation: general aspects of the course at UPF ("plan docente").
• 🎓 Evaluation rules for course at UPF.
• 📆 Calendar for course at UPF.

This course is based on materials by Carlos Castillo.

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

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