Data Science related courses

The following are some courses being offered that are at least vaguely related to Data Science. Please let us know of others that we should list here.

Fall 2016

These are "topics" courses that are not taught regularly or listed with a fixed syllabus in the catalog. These are excellent opportunities to take a cutting-edge course.

Winter 2016

    MAT 271: Applied and Computational Harmonic Analysis, Prof. Naoki Saito
    STA250: Numerical Optimization, Prof. Cho Hsieh
    ECS170: Artificial Intelligene, Prof. Ian Davidson
    ECS230: Applied Numerical Linear Algebra, Prof. Gygi
    ECS271: Machine Learning, Prof. Ian Davidson
    ECS165A: Database Systems, Nitta
    ECS163: Information Interfaces, Kwan-Liu Ma
    ECS188: Ethics and Information Age
    ECS256: Probabilistic Modeling, Prof. Norm Matloff
    MAT128B: Numerical Analysis, Prof. Cheer
    MAT226B: Matrix Computations, Prof. Freund
    MAT235B: Probability Theory, Prof. Soshnikov
    PHY256: Physics of Information and Computation, Prof. Jim Crutchfield
    • Information processing in nonequilibrium thermodynamic systems (greatly extended this year)
    • Information processing in quantum dynamical systems (new this year)
    • Flipped format: Lectures and interactive labs online, meeting times used for problem solving.
    • Winner of SIAM First Prize in Teaching Dynamical Systems

Spring 2016

    ECS188: Ethics and Information Age
    ECS231: Large Scale Scientific Computing, Prof. Bai
    ECS253: Network Theory, Prof. D'Souza

Fall 2015

  • BIM289C - Special Topics in Computational Bioengineering: Genomic Big Data Analysis, taught by Sharon Aviran
  • STA141 - Statistical Computing with R, taught by Duncan Temple Lang
  • ECS171 - Machine Learning, Prof. Ilias Tagkopoulos