New Data Science Course – Winter 2018

By | Educational, News

Computational Data Science
(EECS 598 / BIOINF 505)

A new graduate course that provides an in-depth introduction to computational methods in data science for identifying, fitting, extracting and making sense of patterns in large data sets is now enrolling students for Winter 2018.

Lectures will typically begin with an introduction of a core data science method, followed by the student programming the method computationally with a computer assisting the student by certifying when the program is correct, interleaved with ‘just-in-time’ theory that will expose the student to the mathematics that underpin the methodology. Once the method has been correctly implemented, the students will be given a real world example or ‘success story’ to work with that illustrates when the algorithm ‘works’ as expected, followed by an instructor guided computational exploration of the various subtleties of the algorithm and its weakness.

A full course description, prerequisites and schedule are available.

Please share this announcement with students who might be interested.

U-M students make strong showing at Michigan Datathon

By | Data, Educational, Events, General Interest, Happenings, News

University of Michigan students won first and third places in the Michigan Datathon held Nov. 4, 2017 in the Michigan Union and hosted by Citadel LLC, Correlation One, and the U-M Statistics Department.

1st-place winning team from the University of Michigan:

Ruofei (Brad) Zhao, Statistics Ph.D. student

Zheng Gao, Statistics Ph.D. student

You Wu, Master’s in Applied Statistics student

Kevin Zheng, Sophomore, Computer Science

 

2nd-place team:

Zi Yi, Statistics Master’s student, University of Chicago

Tian Gu, Biostatistics Ph.D. student, University of Michigan

Shuo Zhang, Statistics Master’s student, University of Chicago

Shiyang Lu, Robotics & Naval Architecture and Marine Engineering Master’s student, University of Michigan

 

3rd-place team from the University of Michigan:

Hanbo Sun, Master’s in Applied Statistics student

Xinghui Song, Master’s in Applied Statistics student

Tuo Wang, Master’s in Applied Statistics student

Hang Yuan, Master’s in Applied Statistics student

 

For more, see https://lsa.umich.edu/stats/news-events/all-news/graduatenews/MichiganDatathonWinners0.html

Reading and discussion group:  Data science in understanding and addressing climate change 

By | Educational, Events, General Interest, Happenings

CSCAR announces a reading and discussion group Data science in understanding and addressing climate change that will meet on the third or fourth (depending on the preferences of participants) Friday of every month between 3 and 5 pm. We will discuss reports and significant papers that illuminate fundamental issues in climate change science, policy, and management. The suggested format at this stage is that we discuss one science and one policy (or management) paper or chapter. The focus will be on the spatial (and temporal) dimensions of the issue and we will concentrate more on methods and techniques keeping the requirement for domain knowledge relatively low. We will lay emphasis on the conceptual part of the tools and techniques so that it is accessible to a wider set of participants, but will also get into the technical details.

This is an effort to bring people involved in climate change together from a data science perspective. The idea is to learn together in a fun environment and foster dialogue with a focus on how data science can provide the common ground for mutual learning and understanding.

 We will meet in Rackham, but we will be open to rotating the location. You will be able to participate remotely, if you choose to.

 If you are interested send an email to Manish Verma at manishve@umich.edu

 If you have any suggestion for discussion and reading let us know.  We will include chapters from the IPCC and US global change science programs in our discussion.

MDST – NFL Free Agency Value Prediction Competition Kick-Off – Nov. 9, 6pm

By | Data, Data sets, Educational, Events, Happenings, MDSTPosts, MDSTProjects, News

In this competition, student teams at the University of Michigan will use historical free agent data to predict the value of new contracts signed in the 2018 free agency period. These predictions will be evaluated against the actual contracts as they are signed. This competition is organized by the Michigan Data Science Team (MDST), in collaboration with the Baltimore Ravens and the Michigan Sports Analytics Society (MSAS).  Food will be provided. This is an initial kick-off meeting of the competition.

RSVP

Date, Time

Thursday, November 9 at 6:00 PM EST to Thursday, November 9 at 7:00 PM EST
Add To Google Calendar | iCal/Outlook

Location

Weiser Hall 10th Floor Auditorium
500 Church St, 48104, MI

Host

Michigan Data Science Team

 

 

CSCAR provides walk-in support for new Flux users

By | Data, Educational, Flux, General Interest, HPC, News

CSCAR now provides walk-in support during business hours for students, faculty, and staff seeking assistance in getting started with the Flux computing environment.  CSCAR consultants can walk a researcher through the steps of applying for a Flux account, installing and configuring a terminal client, connecting to Flux, basic SSH and Unix command line, and obtaining or accessing allocations.  

In addition to walk-in support, CSCAR has several staff consultants with expertise in advanced and high performance computing who can work with clients on a variety of topics such as installing, optimizing, and profiling code.  

Support via email is also provided via hpc-support@umich.edu.  

CSCAR is located in room 3550 of the Rackham Building (915 E. Washington St.). Walk-in hours are from 9 a.m. – 5 p.m., Monday through Friday, except for noon – 1 p.m. on Tuesdays.

See the CSCAR web site (cscar.research.umich.edu) for more information.

Info session: Consulting and computing resources for data science — Nov. 8

By | Data, Educational, Events, General Interest, Happenings, HPC

Advanced Research Computing at U-M (ARC) will host an information session for graduate students in all disciplines who are interested in new computing and data science resources and services available to U-M researchers.

Brief presentations from members of ARC Technology Services (ARC-TS) on computing infrastructure, and from Consulting for Statistics, Computing, and Analytics Research (CSCAR) on statistics, data science, and computing training and consulting will be followed by a Q&A session, and opportunities to interact individually with ARC and CSCAR staff.

ARC and CSCAR are interested in connecting with graduate students whose research would benefit from customized or innovative computational or analytic approaches, and can provide guidance for students aiming to do this. ARC and CSCAR are also interested in developing training and documentation materials for a diverse range of application areas, and would welcome input from student researchers on opportunities to tailor our training offerings to new areas.

Speakers:

  • Kerby Shedden, Director, CSCAR
  • Brock Palen, Director, ARC-TS

Date/Time/Location:

Wednesday, Nov. 8, 2017, 2 – 4 p.m., West Conference Room, 4th Floor, Rackham Building (915 E. Washington St.)

Add to Google Calendar

Real estate dataset available to researchers

By | Data, Data sets, Educational, General Interest, Happenings, News

The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major data resource capturing parcel-level information about the property market in the United States.  

The data were licensed from the Corelogic corporation, who have assimilated deed, tax and foreclosure information on nearly all properties in the entire US. Coverage dates vary by county, some county records go back fifty years. Coverage is more comprehensive from the 1990s to the present.

These data will support a variety of research efforts into regional economies, economic disparities, trends in land-use, housing market dynamics, and urban ecology, among many other areas.

The data are available on the Turbo Research Storage system for users of the U-M High Performance Computing infrastructure, and via the University of Michigan Library.

To access the data, researchers must first sign a MOU; contact Senior Associate Librarian Catherine Morse cmorse@umich.edu for more information, or visit https://www.lib.umich.edu/database/corelogic-parcel-level-real-estate-data.

Mini-course: Introduction to Python — Sept. 11-14

By | Data, Educational, Events, General Interest, News

Asst. Prof. Emanuel Gull, Physics, is offering a mini-course introducing the Python programming language in a four-lecture series. Beginners without any programming experience as well as programmers who usually use other languages (C, C++, Fortran, Java, …) are encouraged to come; no prior knowledge of programming languages is required!

For the first two lectures we will mostly follow the book Learning Python. This book is available at our library. An earlier edition (with small differences, equivalent for all practical purposes) is available as an e-book. The second week will introduce some useful python libraries: numpyscipymatplotlib.

At the end of the first two weeks you will know enough about Python to use it for your grad class homework and your research.

Special meeting place: we will meet in 340 West Hall on Monday September 11 at 5 PM.

Please bring a laptop computer along to follow the exercises!

Syllabus (Dates & Location for Fall 2017)

  1. Monday September 11 5:00 – 6:30 PM: Welcome & Getting Started (hello.py). Location: 340 West Hall
  2. Tuesday September 12 5:00 – 6:30 PM: Numbers, Strings, Lists, Dictionaries, Tuples, Functions, Modules, Control flow. Location: 335 West Hall
  3. Wednesday September 13 5:00 – 6:30 PM: Useful Python libraries (part I): numpy, scipy, matplotlib. Location: 335 West Hall
  4. Thursday September 14 5:00 – 6:30 PM: Useful Python libraries (part 2): 3d plotting in matplotlib and exercises. Location: 335 West Hall

For more information: https://sites.lsa.umich.edu/gull-lab/teaching/physics-514-fall-2017/introduction-to-python/