Fall 2016 - Professors Luis Amaral and Adam Pah
Lectures: September 6-9 and 12-15 from 9:30am-12:00pm & 1:30pm-4:30pm in L361.
Overview: Our digital, connected, sensor rich world is generating extraordinary amounts of data (“Big Data”) that are being used to purposes as diverse as teaching a computer to win at Jeopardy or offering taxi alternatives. The skills needed to go from data to knowledge and application, which go under the name of Data Science, are in big demand in industry, government, and academia. This course provides an introduction to the foundational skills needed by data scientists. Prior knowledge of programming is not needed.
Restrictions: Intended primarily for undergraduate students. Other students must contact the instructor. Students will need an up-to-date laptop running Linux, OS X, or Windows 7 or higher. Chromebooks will not be permitted. Prior to the start of the course, students must install several packages and verify that they run properly in their machine. Texts: Lecture materials are available online at http://amaral-lab.org/resources/guides/introduction-python-programming-and-data-science.
Requirements: There will be about 6 homework assignments involving the writing of Python code for solving specific problems. Students’ solutions will be uploaded to a server where they will be unit tested. There will also be a final coding project. All students will be expected to attend lectures and complete in class assignments.
Visit CAESAR to register for the course.
Northwestern News Special Feature, May 2016
A tidal wave of digital information has ushered in a new era of computing and analysis in the 21st century. Data science, or "big data," is affecting every aspect of Northwestern’s learning and research enterprises — among other things, leading to breakthroughs in precision medicine; contributing to a revolution in astronomy with profound insights about the universe; transforming the scope and depth of social science research with significant policy implications, and fueling research about consumer behavior that is affecting how companies do business.
Visit Northwestern News to read more.
Thursday, May 12, 2016
5:30 PM – 8:30 PM
600 Foster, Chambers Hall – Lower Level (Note – New Location)
This is the third in a series of university-wide meetups every month, sponsored by the Northwestern Institute on Complex Systems (NICO)
Following several Programming Bootcamps centered around Python language, the Project Night provides the Northwestern community with a creative venue to collaborate on new and interesting Python-related projects.
Similar “hack” nights are springing up at various academic institutions and in cities across the nation. Coders at all levels are welcome!
Our guest speaker is Chris Pankow from the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA), Northwestern University.
Talk: The Sounds of Merging Black Holes
The first discovery of gravitational waves was a momentous event. With the announcement came a wealth of data release products for public consumption.
As a point of interest, the sensitive frequencies of the instruments used by LIGO are analogous to those of human hearing. With this in mind, I will perform a brief demonstration of how to obtain and transform gravitational wave data (including the detected event itself) and transform it into audio data, all using stock python libraries.
Chris has been a researcher in the field of gravitational-wave astronomy for nearly ten years. His thesis work focused on detection of intermediate mass binary black hole binaries. Since then, he has been interested in many aspects of transient gravitational-wave astrophysics including detection and parameterization of compact binaries. His work at UWM and current research focus at Northwestern supports the rapid measurement of masses and spins of these types of binaries in an effort to better direct other observatories in multi-messenger astronomy.
We are looking to recruit 4-6 Data Science Scholars will join a university-wide initiative advancing Data Science throughout Northwestern, across a number of research areas spanning the physical, chemical, biomedical, behavioral, social, economic, information, and communication sciences. Scholars will have joint-appointments with the Northwestern Institute on Complex Systems and Data Science (NICO) – which coordinates the program – and another Research Center matching their area of expertise. Scholars will be appointed to two-year terms (potentially renewable for a third year). Scholars will receive a competitive stipend and benefits package, and an individual research budget. Starting date is flexible.
The aim of the program is to offer a unique opportunity to expand the Scholars’ domain-focused research portfolio, and simultaneously establish their reputation as leaders in the exploding field of Data Science and Analytics. Applications received by January 31st, 2016 will receive full consideration. Later applications will be considered until all positions are filled.
Check the Funding Programs page for more information.
Northwestern University currently hosts a significant number of faculty engaged and interested in data science. Northwestern’s Office of the Provost and Office of Research have made a financial commitment in order to promote the strengthening of interdisciplinary collaborations around data science with the goal of moving Northwestern forward in this area. Importantly, we are defining data science (and “big data”) not by the absolute size of the data, but by its increase relative to what has been typical in a discipline.
As a result of the University’s commitment, the Data Science Initiative has been granted funds to help faculty already involved or planning to get involved in Data Science. Funds have been allocated for the retaining and hiring of postdoctoral fellows and for the support of current graduate students. We will support on the order of 20 data science projects per year at the level of $10K-$50K in direct costs.
View the Funding Programs page for more information.
Wherever you look, there is talk of the revolution being brought about by "Big Data." But is Big Data just a fad, as its critics contend, or is there something at its core that is here to stay with us?
Well before the term was coined, particle physicists were driven to Big Data challenges by the necessity of their large-scale detectors and produced datasets. Now however, we live in a world where not just the amount, but also the diversity and complexity of digital information continues to grow exponentially. Materials simulations and astronomy images are pushing the boundaries of exploration. Social networks enable the exchange of information between people; medical devices and e-commerce record the exchange of information between people and machines; GPS devices and bar code scanners allow the exchange of information between machines.Read More...