First-year students should not be scared away by the 300-level number. Engineering students are welcome.
The role of computation in the sciences is rapidly growing, driven by advances in silicon-based processors, fiber-optic networks, powerful numerical algorithms, and standards for exchanging and processing data. The fruits of these digital technologies now permeate everyday life, through industries dedicated to social networking, search, e-commerce, on-line gaming, and more.
Building on these and emerging technologies, the 21st century is poised to unleash a new, data-intensive paradigm of scientific discovery that will dramatically enhance the scope and scale of data capture, curation, and analysis. In this new (4th) paradigm, cures for diseases might be found by the collective investigations of scientific agents computing semi-autonomously "in the cloud".
This course will invite students to explore the social and technical development of computing for the sciences, from the ENIAC through the top-500 list of supercomputers and on to Amazon's EC2. Through a selection of readings, discussions with invited guests, and first-hand experimentation, students in the course will learn about an assortment of technologies that underlie modern scientific inquiry, investigate their use by U-M cyber-scientists, and gain an appreciation of the fiscal, political and social challenges imposed by this growing area of scholarship.
Textbook (not ordered through bookstores): The Fourth Paradigm: Data-Intensive Scientific Discovery [Paperback]
Eds., Tony Hey, Stewart Tansley, Kristin Tolle
The book is available for free download at www.fourthparadigm.org
and it can be purchased in paperback from Amazon for $39, or $0.99 for the Kindle reader version.
Publisher: Microsoft Research (October 16, 2009)
There will be additional readings made available as pdf's.
For more information, contact Prof. August (Gus) Evrard, firstname.lastname@example.org.
Grades will be based on the following set of activities:
- Class Participation — 15%;
- Quizzes — 20%;
- Essays/Blog Posts — 35%;
- Group Project — 30%.
Any student whose career interests may involve data analysis, especially of large quantities of data from disparate sources. Informatics majors interested in grid and cloud computing will learn how these technologies are applied in the sciences. Curiosity is more important than past experience in computation.
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