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Loyola University Chicago Data Science
College of Arts and Sciences
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Graduate

Learning Outcomes

  • The ability to manage large data sets in preparation for data science analysis
  • A working knowledge of traditional statistical techniques and the ability to apply these methods to a wide array of real world problems.
  • The ability to perform a data science analysis from beginning to end while adhering to the principles of reproducible research.
  • The ability to program in both the R and Python programming languages.
  • Complete a project demonstrating competence in the field of data science.
    • Non-thesis track: Students will be required to complete a real world data science project prior to graduating from this program, either through our consulting course, an internship, an independent study, or other appropriate project
    • Thesis track: Students will be required to undertake a research project culminating in a thesis

Curriculum (Effective Fall 2022)

Non-thesis Track

Statistics Requirements

  • Applied Regression Analysis: STAT408
  • Categorical Data Analysis: STAT410

Computer Science Requirements

Statistics and Computer Science Eletives

  • Statistics Elective: STAT4XX
  • Computer Science Elective: COMP4XX
  • Statistics or Computer Science Elective: STAT4XX/COMP4XX

Data Science Core

  • Introduction to Data Science: DSCI401 (4 credits)
  • One of the following two courses:
    • Predictive Analytics: STAT488
    • Machine Learning: COMP479
  • Data Science Consulting (capstone): DSCI470 (2 credits)

Note: 30 total credit hours

 

Thesis Track

Statistics Requirements

  • Applied Regression Analysis: STAT408
  • Categorical Data Analysis: STAT410

Computer Science Requirements

Data Science Core

  • Introduction to Data Science: DSCI401 (4 credits)
  • One of the following two courses:
    • Predictive Analytics: STAT488
    • Machine Learning: COMP479

Research

  • Introduction to Data Science Research: DSCI494 (2 credits)
  • Data Science Research: DSCI499 (8 credits)
  • Data Science Thesis: DSCI595 (1 credit)

Note: 30 total credit hours

Learning Outcomes

  • The ability to manage large data sets in preparation for data science analysis
  • A working knowledge of traditional statistical techniques and the ability to apply these methods to a wide array of real world problems.
  • The ability to perform a data science analysis from beginning to end while adhering to the principles of reproducible research.
  • The ability to program in both the R and Python programming languages.
  • Complete a project demonstrating competence in the field of data science.
    • Non-thesis track: Students will be required to complete a real world data science project prior to graduating from this program, either through our consulting course, an internship, an independent study, or other appropriate project
    • Thesis track: Students will be required to undertake a research project culminating in a thesis

Curriculum (Effective Fall 2022)

Non-thesis Track

Statistics Requirements

  • Applied Regression Analysis: STAT408
  • Categorical Data Analysis: STAT410

Computer Science Requirements

Statistics and Computer Science Eletives

  • Statistics Elective: STAT4XX
  • Computer Science Elective: COMP4XX
  • Statistics or Computer Science Elective: STAT4XX/COMP4XX

Data Science Core

  • Introduction to Data Science: DSCI401 (4 credits)
  • One of the following two courses:
    • Predictive Analytics: STAT488
    • Machine Learning: COMP479
  • Data Science Consulting (capstone): DSCI470 (2 credits)

Note: 30 total credit hours

 

Thesis Track

Statistics Requirements

  • Applied Regression Analysis: STAT408
  • Categorical Data Analysis: STAT410

Computer Science Requirements

Data Science Core

  • Introduction to Data Science: DSCI401 (4 credits)
  • One of the following two courses:
    • Predictive Analytics: STAT488
    • Machine Learning: COMP479

Research

  • Introduction to Data Science Research: DSCI494 (2 credits)
  • Data Science Research: DSCI499 (8 credits)
  • Data Science Thesis: DSCI595 (1 credit)

Note: 30 total credit hours