Which Machine Learning Course to take?

CIS 419/519 APPLIED MACHINE LEARNING  

  CIS 519 is an introduction to machine learning (ML)
  with an emphasis on applying ML techniques. It meets together with
  an undergraduate version the same course (CIS 419), which has
  somewhat different homework and project requirements.  CIS 419/519 
  are intended for students who are interested in the practical application 
  of existing machine learning methods to real problems, rather than in 
  the statistical foundations of ML covered in CIS 520. The course generally uses
  python/sklearn/pytorch.


CIS 520 MACHINE LEARNING

  CIS 520 is a more mathematically rigorous course in statistical
  machine learning (ML) that provides the background necessary to
  design and use new ML algorithms.  It requires a basic knowledge of
  linear algebra (matrices, eigenvectors, etc.) and probability and is said to require
  a lot of work. Students planning on doing ML research or taking the
  ML WPE exam should take this course. 

  Lyle Ungar's version is in python/sklearn/pytorch; Shivani Agarwal's is in matlab

CIS 519 is NOT a prerequisite for CIS 520.