At Stanford:
Course Code | Course Name | Instructor |
---|
CME 308 | Stochastic Methods in Engineering | Peter Glynn |
ECON 272 | Intermediate Econometrics III: Methods for Applied Econometrics | Guido Imbens |
EE 364A | Convex Optimization I | Stephen Boyd |
STATS 300A | Theory of Statistics I | Joseph Romano |
STATS 300B | Theory of Statistics II | Tselil Schramm |
STATS 300C | Theory of Statistics III | Emmanuel Candes |
STATS 305A | Applied Statistics I | Trevor Hastie |
STATS 310A | Theory of Probability I | Persi Diaconis |
STATS 361 | Causal Inference | Stefan Wager |
STATS 371 | Applied Bayesian Statistics | Wing H Wong |
CME 302 | Numerical Linear Algebra | Eric Darve |
MS&E 319 | Matching Theory | Amin Saberi |
MS&E 379 | Social Data Analysis | Charles Eesley |
STATS 209 | Introduction to Causal Inference | Dominik Rothenhaeusler |
STATS 264 | Foundations of Statistical and Scientific Inference | Steven Goodman |
At NYU:
(-Ux stands for undergraduate level; -Gx stands for graduate level)
Probability & Statistics
Course Code | Course Name | Instructor |
---|
DS-GA 3001 | Applied Statistics | Yanjun Han |
DS-GA 1020 | Mathematical Statistics | Jonathan Niles-Weed |
DS-GA 3001 | Probability and Statistics 2 | Carlos Fernandez-Granda |
STAT-UB 21 | Introduction to Stochastic Processes | Halina Frydman |
DS-UA 9201 | Causal Inference | Judith Abécassis |
MATH-UA 235 | Probability and Statistics | Antoine Cerfon |
STAT-UB 3 | Regression and Forecasting Model | Lucius Riccio |
Statistical & Machine Learning
Course Code | Course Name | Instructor |
---|
MATH-GA 2840 | Theory of Deep Learning | Arthur Jacot |
DS-GA 3001 | Modern Topics in Statistical Learning Theory | Qi Lei |
CSCI-GA 3033 | Machine Learning for Healthcare | Rajesh Ranganath |
DS-UA 301 | Advanced Techniques in Machine Learning and Deep Learning | Parijat Dube |
CSCI-UA 475 | Predictive Analytics | Anasse Bari |
CSCI-UA 473 | Introduction to Machine Learning | Lerrel Pinto |
Data Science
Course Code | Course Name | Instructor |
---|
CSCI-UA 479 | Data Management and Analysis | Matthew Zeidenberg |
DS-UA 202 | Predictive Analytics | Elisha Cohen |
DS-UA 112 | Introduction to Machine Learning | Pascal Wallisch |
Mathematical & Algorithmic Foundations
Course Code | Course Name | Instructor |
---|
MATH-UA 325 | Real Analysis | Michal Shavit |
MATH-UA 140 | Linear Algebra | Simon Becker |
MATH-UA 123 | Multivariable and Vector Calculus | Daniel Stein |
MATH-UA 120 | Discrete Mathematics | Hasan Oveys |
CSCI-UA 310 | Algorithms | Areeba Ikram |
CSCI-UA 201 | Computer Systems Organization | Hasan Aljabbouli |
CSCI-UA 102 | Data Structures | Anasse Bari |