CERTIFICATE IN APPLIED DATA SCIENCE
2018—2019
Link to WesMaps Courses
Certificate in Applied Data Science
COORDINATOR: DIRECTOR OF QAC
To earn the Applied Data Science Certificate, students must complete seven graded courses and the capstone Data Analysis Practicum.
Course Code  Course Title  Credit Hours 

Select one of the following basic knowledge courses:  1  
Elementary Statistics  
Modeling and Data Analysis: From Molecules to Markets  
Statistics: An ActivityBased Approach  
Applied Data Analysis  
Digging the Digital Era: A Data Science Primer  
An Introduction to Data Journalism  
Select two courses from the following mathematical, statistical and computing foundation courses, each from a different group:  2  
Mathematical Foundations


Vectors and Matrices  
Linear Algebra  
Discrete Mathematics  
Graph Theory  
Statistical Foundations


Quantitative Methods in Economics  
Political Science by the Numbers  
An Introduction to Probability  
Mathematical Statistics  
Computing Foundations


Bioinformatics Programming  
Introduction to Programming  
How to Design Programs  
Computer Science I  
Computer Science II  
Select two of the following applied data science courses:  2  
Exploratory Data Analysis and Pattern Discovery  
Applications of Machine Learning in Data Analysis  
Quantitative Textual Analysis: Introduction to Text Mining  
Select two credits from the following applied electives:  2  
Introduction to GIS  
Advanced GIS and Spatial Analyses  
Economics of Big Data  
Econometrics  
Introduction to Forecasting in Economics and Finance  
Empirical Methods for Political Science  
Advanced Topics in Media Analysis  
Computational Physics (0.5 credits)  
Applied Quantitative Methods in Survey Research  
Introduction to (Geo)Spatial Data Analysis and Visualization  
Introduction to Network Analysis  
Data Visualization: An Introduction  
Experimental Design and Causal Inference  
Longitudinal Data Analysis (0.5 credits)  
Hierarchical Linear Models (0.5 credits)  
Latent Variable Analysis (0.5 credits)  
Survival Analysis (0.5 credits)  
Bayesian Data Analysis: A Primer (0.5 credits)  
Advanced R: Building OpenSource Tools for Data Science  
Introduction to Statistical Consulting  
NOTE: at least one of the electives should be a 300 level course


The capstone Data Analysis Practicum that includes an ethics and epistemology seminar discussion as well as completing an independent data science project.  1 
ADDITIONAL INFORMATION
 Some of the courses that count toward the certificate may have a prerequisite, such as calculus. These prerequisites do not count toward the certificate, and students attempting to complete the certificate are not recused from these prerequisites.
 Mathematics majors cannot count courses in the foundations groups already covered by their major toward the certificate. They must instead complete one course from the statistical foundations group and complete three applied elective courses. Alternatively to completing three applied elective courses, they can take either MATH232 or COMP212 and complete two applied elective courses.
 Computer science majors cannot count courses in the foundations groups already covered by their major toward the certificate. They must instead complete one course from the statistical foundations group and complete three applied elective courses. Alternatively, they can complete both MATH231 and MATH232 and complete two applied elective courses.
 It is strongly recommended that students who are not mathematics or computer science majors take courses in the computing foundations group to satisfy the certificate requirements. They can also substitute either MATH232 or COMP212 for one of their applied elective courses.
 Economics majors and minors cannot count ECON300 toward the certificate and must instead complete one course from each of the other two foundation groups.
 Students cannot count more than one course towards this certificate that also counts toward completion of any of their majors or minors.
 Up to two courses taken elsewhere may substitute as appropriate for any of the above courses and count toward the certificate, subject to the QAC Advisory Committee’s approval (where routine approval may be delegated to the QAC director).
 Students can substitute a course from among the applied data science and applied elective courses for the basic knowledge course, subject to approval.
 Students cannot receive both the data analysis minor and the applied data science certificate.