Courses Approved to meet the AMS Master’s/Ph.D. Computing Requirement

Students typically meet this requirement by receiving a grade of B- or better in taking an approved AMS department course. The list of approved courses together with the years in which versions of these courses can be used to meet the requirement is:

 

  • 110.445 Mathematical and Computational Foundations of Data Science (Spring 2020 or later)
  • 553.600 Mathematical Modeling and Consulting (Fall 2017 or later)
  • 553.613  Applied Statistics and Data Analysis (Fall 2017 or later)
  • 553.632/553.732 Bayesian Statistics (2015 or later)
  • 553.633  Monte Carlo Methods (Fall 2017 or later)
  • 553.636 Data Mining (Fall 2017 or later)
  • 553.643  Financial Computing in C++ (Fall 2017 or later)
  • 553.650 Computational Molecular Medicine (Fall 2017 or later)
  • 553.687 Numerical Methods for Financial Mathematics (Fall 2017 or later)
  • 553.688 Financial Computing I (Fall 2017 or later)
  • 553.689 Financial Computing II (Spring 2018 or later)
  • 553.693  Mathematical Image Analysis (Fall 2017 or later)
  • 553.740 Machine Learning (Fall 2018 or later)
  • 553.741 Machine Learning II (Spring 2020 or later)
  • 553.743 Graphical Models (2007 or later)
  • 553.753 Commodities and Commodity Markets (2013 or later)
  • 553.761 Foundations in Optimization/Nonlinear Optimization I (2012 or later)
  • 553.762 Optimization Algorithms/Nonlinear Optimization II (2007 or later)
  • 553.763 Stochastic Search and Optimization (Spring 2018 or later)
  • 553.765 Convex Optimization (2016 or later)
  • 553.780 Shape and Differential Geometry (2015 or later)
  • 553.681/553.781 Numerical Analysis (2007 or later)
  • 601.675 Introduction to Machine Learning (Fall 2017 or later)
  • 601.682 Machine Learning:Deep Learning (Spring 2018 or later)

 

Courses Approved through Spring 2017 or earlier only.

  • 550.400 Mathematical Modeling and Consulting (Fall 2008 – Spring 2017)
  • 550.413 Applied Statistics and Data Analysis (2007 – Spring 2017)
  • 550.415 Practical Scientific Analysis of Big Data (2015 – Spring 2017)
  • 550.433 Monte Carlo Methods (2007 – Spring 2017)
  • 550.436 Data Mining (2007 – Spring 2017)
  • 550.443 Financial Computing in C++ (2015 – Spring 2017)
  • 550.450 Computational Molecular Medicine (2012 – Spring 2017)
  • 550.480 Shape and Differential Geometry (2007 – 2014)
  • 550.487 Numerical Methods for Financial Mathematics (2013 – Spring 2017)
  • 550.493 Mathematical Image Analysis (2007 – Spring 2017)
  • 550.640 Machine Learning (2007 – Spring 2017)
  • 600.475 Introduction to Machine Learning (2014 – Spring 2017)
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