Loyola University Maryland

Data Science

Curriculum

All coursework offered at Columbia Graduate Center. Most courses are hybrid. This will mean that some weeks will substitute synchronous in classroom learning for asynchronous out-of-classroom learning.

The program consists of 10 courses. The requirements include the following. 

  • Four core courses in business, statistics, and computer science. 
  • Two additional statistics courses. 
  • Two additional computer science courses;. 
  • An elective from statistics, computer science, or business. 
  • A technical capstone project. 

For the required statistics and computer science courses, one course is proscribed while the other is an elective.

For course descriptions, please see the Graduate Catalog.

Core

  • CS703 Programming for Data Science (taught by CS faculty)
  • ST710 Statistical Computing (taught by Statistics faculty)
  • DS730 Introduction to Data Science
  • DS851 Business Intelligence and Data Mining (taught by IS faculty)

Additional Required Courses

  • CS737 Machine Learning
  • ST765 Linear Statistical Models
  • DS795/796 Data Science Project

Computer Science Elective Courses

  • CS745 Multimedia data analysis and mining
  • CS746 Data Visualization
  • CS750 Special Topics in Computer Science
  • CS751 Independent Study  
  • CS765 Database Retrieval
  • CS766 Information Retrieval and Natural Language Processing

Statistics Elective Courses

  • ST767 Multivariate Analysis
  • ST775 Generalized Linear Models and Multilevel Models
  • ST776 Bayesian Inference
  • ST778 Time Series
  • ST791 Special Topics in Statistics
  • ST792 Independent Study

Business Elective Courses

  • GB700 Ethics and Social Responsibility
  • GB701 Operations Management and Process Strategies
  • GB705 Leadership and Management
  • GB732 Data Management and Governance
  • GB733 Enterprise Systems
  • GB736 Data Visualization for Decision Making
  • GB852 Advanced Analytics
  • GB853 Social Media and Web Mining
  • GB735 Project Management