PIMS-CANSSI-SSC-USaskatchewan

Data Science Bootcamp, June 10-21, 2019

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The
University of Saskatchewan will hold its inaugural Data Science
Bootcamp from June 10 -21, 2019. This
Bootcamp is intended for graduate and senior undergraduate students; a
limited number of non-students will also be accepted to participate. Description Data science is an
interdisciplinary field that combines perspectives from mathematics,
statistics and computer science. The focus is to extract and
communicate meaningful information from complex data using techniques
that fall under the umbrella of these three disciplines. The scope of
the field is expanding, as learning from data is common practice in all
disciplines. With the increasing availability of data with wide ranging
characteristics, there is now a high demand for data scientists.
The summer school will expose participants to some core areas
of data science, including real data analysis and hands-on training in
software. After successful completion of the program, a participant is
expected to have a working knowledge of data science, including basic
concepts and ideas, problem solving skills, computer programming, and
in general, tools for extracting and communicating meaningful
information from complex data.
Location University of Saskatchewan Topics - Introduction to Machine Learning
- Statistical Methods for High-throughput Data
- Data Visualization
- Data Science Case Studies
With a focus on graduate-level students with a research interest in data science, it is recommended students have some familiarity with basic concepts from linear algebra, calculus, probability and hypothesis testing, and some experience with computer programming and statistical software packages. Organizers Shahedul Khan, University of Saskatchewan, khan@math.usask.ca Longhai Li, University of Saskatchewan, longhai@math.usask.ca Juxin Liu, University of Saskatchewan, liu@math.usask.ca Annaliza McGillivray, University of Saskatchewan, mcgillivray@math.usask.ca Cindy Feng, University of Saskatchewan, cindy.feng@usask.ca Nathaniel Osgood, University of Saskatchewan, osgood@cs.usask.ca Debajyoti Mondal, University of Saskatchewan, d.mondal@usask.ca Lisa Lix, University of Manitoba, Lisa.Lix@umanitoba.ca Andrei Volodin, University of Regina, Andrei.Volodin@uregina.ca Volunteers Jafar Farsani, School of Public Health, University of Saskatchewan Zahida Irin, Department of Mathematics and Statistics, University of Saskatchewan Jian'ou Zhang, Department of Mathematics and Statistics, University of Saskatchewan Kangjie Zhang, Department of Mathematics and Statistics, University of Saskatchewan Contact data-science@math.usask.ca |