Description
The ACMS Data Science and Statistics option is designed with strong statistics and applied mathematics components. The track incorporates coursework in mathematical modeling and scientific computation, statistical learning, probability and data science. Students graduating with the major will be well prepared for careers in data science, technology and government sectors, or for further graduate studies in the quantitative sciences.


Option Core (44-56 credits)

Core Courses (15-16 credits)

1. Probability: MATH/STAT 394** (3) Probability I

2. Introductory Statistics (One of): 

  • STAT 290** (5) AP Statistics  
  • STAT 311** (5) Elements of Statistical Methods or

3. Scientific Computing (One of): 

  • AMATH 301** (4) Beginning Scientific Computing   
  • STAT 302** (3) Statistical Software and Its Applications

4. Data Programming: CSE 163 (4) Intermediate Data Programming

Data Science (11-14 credits)

1. Ethics (One of):

  • STAT 303 (3) Introduction to the Ethics of Algorithmic Decision Making
  • SOC 225 (3 or 5) Data and Society
  • INFO 351 (4) Information Ethics and Policy

2. Database (One of):

  • CSE 414 (4) Introduction to Database Systems
  • INFO 330 (5) Databases and Data Modeling

3. Machine Learning (One of):

  • STAT 435 (4) Introduction to Statistical Machine Learning
  • CFRM 421 (4) Machine Learning for Finance

Scientific Computing & Optimization (6-8 credits)

Take one course from at least two items below

  • AMATH 481 (5) Scientific Computing  or  AMATH 482 (5) Computational Methods for Data Analysis
  • MATH 464 (3) Numerical Analysis
  • MATH 407 (3) Linear Optimization

Statistics (12 credits)

  • STAT 391 (4) Quantitative Introductory Statistics for Data Science

      Two of the following:

  • STAT 425 (4) Introduction to Nonparametric Statistics  or  STAT 403 (4) Introduction to Resampling Inference
  • STAT 451 (4) Visualizing Data  or  CSE 412 (4) Introduction to Data Visualization
  • STAT/IND E 316: (4) Design of Experiments

Option electives (3 courses, 9-13 credits)

Any course listed above can be an elective, unless it is used towards a requirement. Can also choose from the pre-approved list below.

  • STAT 428: (4) Multivariate Analysis for the Social Sciences
  • STAT 427: (4) Introduction to Analysis of Categorical Data
  • STAT 441: (4) Multivariate Statistical Methods
  • 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
  • MATH 300: (3) Introduction to Mathematical Reasoning
  • MATH 318: (3) Advanced Linear Algebra 
  • MATH 327: (3) Introduction to Real Analysis
  • MATH 381: (3) Discrete Mathematical Modeling
  • MATH 424/425/426: (3) Fundamental Concepts of Analysis
  • MATH/STAT 395/396/491/492: (3) Probability and Stochastic Processes
  • MATH 408/409: (3) Optimization
  • MATH 465: (3) Numerical Analysis
  • PHYS 417: (3) Neural Network Methods for Signals in Engineering and Physical Sciences
  • AMATH 383: (3) Math modeling 
  • AMATH 483: (5) High Performance computing

Courses with ** would indicate demonstrated interest in this degree option, if taken prior to applying to the ACMS program.

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.