Data Sciences and Statistics

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.

• ACMS Program Core (38-39 credits)

 
Students in the Data Science and Statistics option will substitute Math/Stat 394 for Math/Stat 390.

Option Core (29-30 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) High-Performance 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.