Data Science Concentration

  1. To combine mathematics, statistics, and computing into an integrated curriculum, providing students the rigorous theoretical background of data science methods and techniques necessary for success in data-related fields in addition to just knowing how to implement them; and
  2. To synthesize the analytical skills and mathematical knowledge to analyze data, draw conclusions, and make decisions in real-life situations.


Concentration Required Courses  6 units
  MATH3836 Data Mining 3 units
  MATH4225 Foundation of Big Data and Learning 3 units
Concentration Elective Courses  15 units
  Group A   
  Choose at least two courses of the following courses:  
  MATH4226 Introduction to Deep Learning 3 units
  MATH4227 Programming for Data Science 3 units
  MATH4815 Interior Point Methods for Convex Optimization 3 units
  MATH4816 Optimization Theory and Techniques 3 units
  Group B  
  Choose at least one course of the following courses:  
  MATH3427 Real Analysis 3 units
  MATH3605 Numerical Methods II 3 units
  MATH3615 Introduction to Imaging Science 3 units
  MATH3626 Computational Statistics for Data Science 3 units
  MATH3826 Markov Chain and Queuing Theory 3 units
  MATH4615 Introduction to Numerical Linear Algebra 3 units
  MATH4807 Categorical Data Analysis 3 units
  MATH4826 Time Series and Forecasting 3 units
  MATH4875 Special Topics in Statistics I 3 units
  MATH4876 Special Topics in Statistics II 3 units
  MATH4877 Special Topics in Statistics III 3 units
    21 units


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