About this course
Networks are everywhere! We find them in transportation systems that connect cities throughout the world, in the web of interactions within our cells, in the vast expanse of the World Wide Web that powers our daily searches, and even in the social relationships that define our communities. They are crucial for understanding why certain webpages appear at the top of your Google searches or why a specific song is suggested to you on Spotify.
In this course, you will dive into the world of complex networks. You will explore computational and mathematical methods used to characterize, represent, and analyze these intricate systems. Using a hands-on approach, the Python programming language, and the NetworkX library, you will model, visualize, analyze, and extract insights from real-world networks.
Syllabus
Pre-requisites
One year of computer science at university level. One of the computer science courses should be in algorithms and data structures. Knowledge of at least one programming language (e.g. Python/Javascript/Java/C++/Matlab). A course in probability is recommended.
Short Study Tour
About this tour
Alongside two days of seminars and workshops in Copenhagen, you will travel on a three-day Study Tour in Denmark, to gain insight into the use of data and their representation into networks. You will have the opportunity to discuss and understand the challenges of the field and hear from the experiences of scientists and other professionals, both in industry and academic institutions. Together, we will see how what we have learned in class is used in the real-world for decision making and how it plays an important part in understanding the underlying structures of data and the relationships of the various data entities.
The program is supplemented with cultural visits to help you learn more about Danish history and culture along the way, experiencing life outside the capital region. Some cultural visits will include touring art museums, visiting historical sites, and enjoying traditional Danish food.
Learning outcomes
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Gain insight to the translation of complex networks and computer science in general from academia to industry
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Hear about the techniques and tools that are most heavily involved within the profession
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Engage in your personal learning process outside the classroom by actively applying the concepts we learn in class on various “seemingly unlikely” settings and challenge thus your current ideas and assumptions
- Get to know your fellow students and professor in an educational and social setting outside DIS
Possible activities
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Learn how complex networks are used in research at the Novo Nordisk Foundation CO2 Research Center
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Visit Odense Robotics – a high-tech cluster of robot and automation companies
- Meet with professors and scientists at Danish Higher Education institutes, such as Aarhus University and SDU
Long Study Tour
