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.