Loyola University Maryland

Data Science

Major

Bachelor of Science (B.S.) in Data Science 

Data Science is a growing field that blends computer science, statistics, and information systems with domain knowledge to extract knowledge from data to solve real problems. As such, it provides foundational skills in statistical analysis, programming, and business. Students will gain deep analytic knowledge that will make them well qualified to assume roles such as business analysts, domain-specific managers, data mining analysts, business intelligence specialists, and managers of analytics in an organization. Data scientists are in high demand and the demand promises to continue. 

The interdisciplinary program consists of fifteen (15) courses providing students the analytical, and computational skills required within the domain of data science. 

Data Science Major Courses

Required Courses (12 required courses)

CS151 - Computer Science 1 (Core)
CS295 - Discrete Structures or MA295 - Discrete Structures or MA395 - Discrete Methods
MA303/PH303/CS403/DS303 - Data and Information
IS251/BH251 - Data Analytics and Information Systems
IS353 - Data Management and Database Systems or CS485 - Database Management Systems
IS358 - Business Intelligence and Data Mining 
MA251 - Calculus I (Core) (or MA151 with permission of the program director)
ST210 - Introduction to Statistics or ST265 - Biostatistics or EC220 - Business Statistics
ST310 - Statistical Computing
ST465 - Experimental Research Methods
ST472 - Applied Multivariate Analysis
DS496 - Ethical Data Science Capstone

Electives (choose 3 courses)

CS312- Object-Oriented Software Design
CS484 - Artificial Intelligence
CS487 - Big Data
IS453 - Information Systems Analysis and Design
IS460 - Data Visualization
IS465 - Text Mining
MA301 - Linear Algebra
ST461 - Elements of Statistical Theory I: Distributions (MA351 is a prerequisite)
ST466 - Experimental Design
EC420 - Econometrics
EC 425 - Applied Economic Forecasting
Or appropriate course approved by program director (Eg GIS)

Up to 2 graduate DS courses may be taken with approval from the graduate director

An internship as DS499 may be taken for university credit, but does not count as an elective in the BS DS. It is not anticipated that this course would substitute for the capstone as the ethical component in the capstone is particularly important. This aspect would not necessarily be present in the internship. Instead it is expected that the internship experience may enhance the capstone experience for the student by providing the relationship from which the student can develop the capstone project.

It is recommended that students take EC102 and EC103 for their social science core.

Sample Four-Year Undergraduate Curriculum

First Year

Fall Term
MA251 - Calculus I
CS151 - Computer Science 1
Social Science Core (EC102 recommended)

Spring Term
ST210 - Introduction to Statistics or ST265 - Biostatistics  or EC220 - Business Statistics
IS251 - Information Systems or BH 251 - Information Systems
Social Science Core (EC103 recommended)

Sophomore Year

Fall Term
CS295 - Discrete Structures or MA295 - Discrete Structures or MA395 - Discrete Methods
DS303/MA303/PH303/CS402 - Discovering Information in Data

Spring Term
ST310 - Statistical Computing
IS353 - Data Management and Database Systems or CS485 - Database Management Systems

Junior Year

Fall Term
ST465 - Experimental Research Methods
IS358 - Business Intelligence and Data Mining

Spring Term
ST472 - Applied Multivariate Analysis
DS Program Elective

Senior Year

Fall Term
DS Program Elective
DS Program Elective
 
Spring Term
DS496 - Ethical Data Science Capstone