Schedule of Classes: Applied Mathematics & Statistics: 2019-2020


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Please note that the course schedule and offerings are subject to change.

« Back to 2018-2019

Fall 2019 Winter 2020 Spring 2020 Summer 2020
AMS3: Precalculus for the Social Sciences
AMS5: Statistics
AMS6: Precalculus for Statistics
Note: Previously AMS 2: Pre-Statistics
AMS7: Statistical Methods for the Biological, Environmental, and Health Sciences
AMS7L: Statistical Methods for the Biological, Environmental, and Health Sciences Laboratory
AMS10: Mathematical Methods for Engineers I
AMS10A: Basic Mathematical Methods for Engineers I
AMS11A: Mathematical Methods for Economists I
AMS11B: Mathematical Methods for Economists II
AMS15A: Case-Study Calculus I
AMS15B: Case-Study Calculus II
AMS20: Mathematical Methods for Engineers II
AMS20A: Basic Mathematical Methods for Engineers II
AMS27L: Mathematical Methods for Engineers Laboratory
AMS80A: Gambling and Gaming
AMS80B: The Art of Data Visualization
Fall 2019 Winter 2020 Spring 2020 Summer 2020
AMS100: Mathematical Methods for Engineers III
AMS107: Introduction to Fluid Dynamics
AMS113: Managerial Statistics
AMS114: Introduction to Dynamical Systems
AMS115: Stochastic Modeling in Biology
AMS129: Foundations of Scientific Computing for Scientists and Engineers
AMS131: Introduction to Probability Theory
AMS132: Classical and Bayesian Inference
AMS147: Computational Methods and Applications
AMS148: GPU Programming for Scientific Computations
AMS156: Linear Regression
AMS162: Design and Analysis of Computer Simulation Experiments
Fall 2019 Winter 2020 Spring 2020 Summer 2020
AMS200: Research and Teaching in AMS
AMS202: Linear Models in SAS
AMS203: Introduction of Probability Theory
AMS204: Introduction to Statistical Data Analysis
AMS205: Introduction to Classical Statistical Learning
AMS205B: Intermediate Classical Inference
AMS206: Applied Bayesian Statistics
AMS206B: Intermediate Bayesian Inference
AMS207: Intermediate Bayesian Statistical Modeling
AMS211: Foundations of Applied Mathematics
AMS212A: Applied Mathematical Methods I
AMS212B: Applied Mathematical Methods II
AMS213: Numerical Solutions of Differential Equations
AMS213A: Numerical Linear Algebra
AMS213B: Numerical Methods for the Solution of Differential equations
AMS214: Applied Dynamical Systems
AMS215: Stochastic Modeling in Biology
AMS216: Stochastic Differential Equations
AMS217: Introduction to Fluid Dynamics
AMS221: Bayesian Decision Theory
AMS223: Time Series Analysis
AMS225: Multivariate Statistical Methods
AMS227: Waves and Instabilities in Fluids
AMS229: Convex Optimization
AMS230: Numerical Optimization
AMS231: Nonlinear Control Theory
AMS232: Applied Optimal Control
AMS236: Motion Coordination of Robotic Networks
AMS238: Fundamentals of Uncertainty Quantification in Computational Science and Engineering
AMS241: Bayesian Nonparametric Methods
AMS245: Spatial Statistics
AMS250: An Introduction to High Performance Computing
AMS256: Linear Statistical Models
AMS260: Computational Fluid Dynamics
AMS261: Probability Theory with Markov Chains
AMS263: Stochastic Processes
AMS266A: Data Visualization and Statistical Programming in R
AMS266B: Advanced Statistical Programming in R
AMS266C: Introduction to Data Wrangling
AMS268: Advanced Bayesian Computation
AMS274: Generalized Linear Models
AMS275: Magnetohydrodynamics
AMS276: Bayesian Survival Analysis and Clinical Trial Design
AMS280A: Seminar in Mathematical and Computational Biology
AMS280B: Seminars in Statistical and Applied Mathematical Modeling
AMS280C: Seminar in Geophysical & Astrophysical Fluid Dynamics
AMS280D: Seminar in Bayesian Statistical Methodology
AMS285: Seminar in Career Skills
AMS290A: Topics in Mathematical and Computational Biology
AMS290B: Advanced Topics in the Numerical Solution of PDEs
AMS291: Advanced Topics in Bayesian Statistics