CSML Course Trees

The course trees shown below are designed to help you understand the range of Princeton courses offered in Data Sciences, Machine Learning, Optimization, Probability and Statistics, and to assist students and faculty advisors in planning course selections.  All of the courses listed are full semester, graded courses.

Please note that courses may not be offered every semester nor every year. In addition, some courses have limited enrollment and fill up quickly. To check if a course is being courses offered in a particular semester, and its enrollment cap, please check the Registrar’s website, or the website of the home department. 

If you have any questions or see any errors or omissions, please send us an email.  


Machine Learning


Machine Learning Course Tree

  • The following ML courses are cognates: ELE 435, ELE 535
  • Except for the cognate courses above, the following ML courses are complementary: COS 324, ORF 350, COS 424, ELE 435, COS 485, COS 511, COS 513, ELE 535, ELE 571
  • ELE 364 can be taken as an introduction to ML prior to taking courses from the list above.  However, it doesn’t make sense to first take a more advanced ML course and then take the introductory course ELE 364.

 


Data Science, Statistics, Probability


Statistics Course Tree

  • Modern statistics frequently relies on programming and high-performance computing.  Introductory data science and statistics courses employing a programing language are helpful for students intending to pursue advanced courses or research projects in data science. The following codes are used in the chart:
    • (R) indicates a course using the programing language R.                            
    • (+R) indicates a course that teaches and uses R.                     
    • (P) indicates a course using the programing language Python.
    • Other statistics packages include STATA and SPSS.
  • The following statistics courses differ in style, application domains, and some advanced topics, but have sufficient overlap to be considered as cognates: ECO 202, ORF 245, POL 345/SOC 305, PSY 251, WWS 200
  • SML 201 teaches R and covers introductory statistics. Taking SML 201 before taking a more advanced statistics courses makes sense. Taking these courses in the reverse order is not recommended.

 


Optimization


 

optimization course tree