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College of Arts and Sciences Department of Mathematics and Statistics

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Mathematics and Statistics

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Minor in Data Science

CAS  >  Departments  >  Mathematics and Statistics  >  Programs  >  Minor in Data Science

The Minor in Data Science provides students with essential knowledge of data analytics and skills. The program covers a wide range of topics including data preparation and visualization, statistical modeling, programming, machine learning and data mining techniques.

On completion of the program, students will be able to:

  • formulate and build statistical models for various real-life applications
  • apply relevant programming skills using professional data mining software such as R, Python and SAS
  • analyze big data using various data science techniques
  • demonstrate skills in interpreting and communicating the results of data analysis, orally and in writing

Students enrolling in the data science minor should have normally completed a minimum of 30 credit hours of course work and be in good academic standing.

The following rules apply:

  • The minor consists of a minimum of 18 credit hours, including at least nine credit hours in courses at or above the 300 level.
  • At least nine credit hours of the 18 credit hours required for the minor must be successfully completed in residence at AUS.
  • At least six credit hours of the nine credit hours at or above the 300 level must be successfully completed in residence at AUS.
  • A minimum GPA of 2.00 must be earned in courses completed to satisfy the minor.

Students seeking a minor in data science must successfully complete the following courses or their equivalent. All course prerequisites must be satisfied.

Minor Requirements (12 credit hours)

  • CMP 120 Programming I or MIS201 Fundamentals of Management Information Systems
  • one of the following:
    • STA 201 Introduction to Statistics for Engineering and Natural Sciences
    • STA 202 Introduction to Statistics for Social Sciences
    • QBA 201 Quantitative Business Analysis
    • NGN 111 Introduction to Statistical Analysis, plus MTH 243 Introduction to Mathematical Programming or a one-credit CMP or COE directed study in data science
  • STA 301 Foundations of Statistics for Data Science
  • STA 401 Introduction to Data Mining or CMP 466 Machine Learning and Data Mining or MIS 388 Business Analytics

Minor Electives (minimum of 6 credit hours)

Students must successfully complete a minimum of six credit hours in courses selected from the following list. A minimum of three credit hours must be successfully completed in courses at the 300-level or above.

  • CMP 305 Data Structures and Algorithms
  • CMP 320 Database Systems
  • CMP 433 Artificial Intelligence
  • COE 375 Modeling and Simulation of Stochastic Systems or ELE 360 Probability and Stochastic Processes for Electrical Engineers
  • ECO 351 Introduction to Econometrics
  • ECO 451 Advanced Econometrics
  • ELE 456 Pattern Recognition
  • FIN 430 Financial Forecasting
  • INE 415 Design of Experiments
  • MCM 311 Mass Communication Research Methods and Data Analytics
  • MIS 301 Fundamentals of Database Management
  • MTH 221 Linear Algebra
  • MTH 350 Introduction to Probability
  • MTH 382 Linear Programming and Optimization
  • MTH or STA 394/494 approved special topic courses in the areas of probability, optimization and statistics
  • STA 233Introduction to Survey Sampling and Analysis
  • UPL 302 Analysis of Spatial Phenomena

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