Description
The ACMS Data Sciences and Statistics option is designed with strong Statistics and Modeling components. The track incorporates coursework in Computation, Statistics and Machine Learning, Databases and Data Visualization, as well as topics related to science and society. This option is unique in its double emphasis on Statistics and Modeling & Scientific Computing. Our graduates will have a unique blend of skills to build models for data, use them efficiently, and interpret them statistically.
Students in the Data Science and Statistics option will substitute Math/Stat 394 for Math/Stat 390.
Option Core (2930 credits)
 PHYS 121, 122, 123 (5,5,5)

Either:
 AMATH 301: (4) Beginning Scientific Computing or
 STAT 302: (3) Statistical Software and Its Applications
 MATH/STAT 395: (3) Probability II
 STAT 391: (4) Quantitative Introductory Statistics for Data Science
 CSE 414: (4) Introduction to Database Systems
Option Electives (18 credits)
Group I
At least 6 credits from (List A):
 STAT 403: (4) Intro to Resampling Inference
 STAT 421: (4) Applied Statistics and Experimental Design
 STAT 423: (4) Applied Regression and Analysis of Variance
 STAT 428: (4) Multivariate Analysis for the Social Sciences
 STAT 435: (4) Introduction to Statistical Machine Learning
 MATH/STAT 396: (3) Probability III
 BIOST/STAT 425: (3) Introduction to Nonparametric Statistics
 STAT 427: (4) Introduction to Analysis of Categorical Data
 STAT 441: (4) Multivariate Statistical Methods
 MATH/STAT 491: (3) Introduction to Stochastic Processes
At least 6 credits from (List B):
 AMATH 481: (5) Scientific Computing
 AMATH 482: (5) Computational Methods for Data Analysis
 AMATH 483: (5) HighPerformance Scientific Computing
 MATH 464: (3) Numerical Analysis I
 MATH 465: (3) Numerical Analysis II
 MATH 407: (3) Linear Optimization
 MATH 408: (3) Nonlinear Optimization
 MATH 409: (3) Discrete Optimization
 CSE 373: (4) Data Structures and Algorithms
 CSE 415: (3) Introduction to Artificial Intelligence
 CSE 417: (3) Algorithms and Computational Complexity
 CSE 472: (5) Introduction to Computational Linguistics

HCDE 411: (5) Information Visualization OR CSE 412: (4) Introduction to Data Visualization.
 Students who choose to use CSE 412 will need to email us at: advising@math.washington.edu so it can be added to your DARS
Group II (List C)
At least 6 additional credits at the 300 level or higher from any courses that receive a numeric grade in AMATH, CSE, MATH or STAT departments. The courses listed above in Group I are particularly recommended. STAT 311 is prohibited as ACMS students take more rigorous statistics courses. We advise ACMS majors to run a degree audit or plan audit in MyPlan to confirm a course can be used as an option elective.
Sample Graduation Plan:
A sample plan for ACMS DSS students can be found here. Your plan may differ from this, however it is critical to note prerequisites and when courses are offered. The ACMS DSS option takes two years to complete, assuming you begin Math/Stat 394 in Autumn of your junior year.