Course Detail: CMP422 - Introduction to Network Science - NEW!
Figure 1: A directed network visualizing the dependencies between crafting objects in Minecraft.
Introduction to Network Science
This is a credit course offered with a noncredit option to complete. To complete as noncredit, please register below.
Prerequisite: Students should have a deep level of understanding of linear algebra, probability, and statistics.
Registration Deadline: August 16, 2023.
Required Materials: Students will need to purchase the following book. It is not included in the course fee.
Networks (2nd edition). Mark Newman. Oxford University Press, 2018. ISBN: 978-0198805090
Who should attend: Designed for undergraduate, graduate, and professionals in computer science, mathematics, data science, and business analytics. This includes marketing professionals with the required prerequisite knowledge.
Incorporate the transformative potential of network science into your advertising, marketing, and media strategies, empowering you to deliver targeted campaigns that effectively reach and engage your clients' desired audiences. Leverage the intricate network dynamics to optimize message dissemination, identify key influencers, and enhance the overall impact of your clients' brand communications.
Expand your horizons and delve into the fascinating world of network science with our introductory course. This course will equip you with the essential knowledge, skills, and applications of network science.
Network science finds applications in various fields, showcasing its versatility and wide-ranging impact. In social sciences, it helps us understand the dynamics of social networks, analyze the spread of information, and study social influence and opinion formation. In biology, network science unravels intricate biological networks like protein interactions, gene regulatory networks, and brain connectivity, aiding in disease detection and drug discovery. In transportation and infrastructure, it optimizes routing algorithms, uncovers critical nodes for efficient resource allocation, and improves urban planning. In business, the interconnected nature of markets, customers, and information makes network analysis a powerful tool for understanding and optimizing business strategies in today's complex and dynamic environment. Moreover, network science has found relevance in computer science, finance, epidemiology, ecology, and countless other domains, highlighting its vital role in uncovering the complex interconnections that shape our world.
Under the expert guidance of Dr. Drake Olejniczak, you will:
- Explore the theory, methods, and real-world applications of networks.
- Gain a comprehensive understanding of network structures, dynamics, and functionality in social, biological, and technological systems.
- Collaborate with a colleague to create a network of your choice.
- Visualize, analyze, and explore your network utilizing expert level tools such as Gephi and the Python library NetworkX
- Gain hands-on experience applying a wide range of course topics, such as centrality, community detection, random graph models, and diffusion processes, to reveal hidden connections and gain insight into your topic of choice.
About the Instructor:Dr. Drake Olejniczak earned his Ph.D. in Mathematics from Western Michigan University, specializing in Combinatorics and Graph Theory. With a strong research background, Drake has contributed to several published papers in refereed journals, covering topics such as round-robin tournament schedules, Ramsey numbers, and spanning trees. His expertise and passion for mathematics drive his commitment to teaching and mentoring students. Drake is dedicated to fostering a collaborative learning environment and exploring the applications of mathematical principles in real-world contexts.
