Professional Master's Degree Requirements
Our Professional Master's in Data Science and Applied Statistics is designed for flexibility. All students in the Professional Master’s Program complete certificates in Statistical Foundations and Computational Tools, along with a professional development course and a capstone project. Students may choose to specialize by completing a certificate in Computational Biology or Earth Science. Those who do not select a specialization follow the General Track to complete their degree requirements.
General (9 units)
BIOS 647 Categorical Data Analysis
BIOS 648 Analysis of High Dimensional Data
BIOS 684 Mixed Effects Models and Longitudinal Data
CSC 535 Probabilistic Graphical Models
STAT 568 Applied Stochastic Processes
STAT 571A Advanced Statistical Regression Analysis
STAT 574B Bayesian Statistical Theory and Applications
Statistical Foundations Certificate
MATH 509D Statistics for Data Science
STAT 675 Statistical Computing
MATH 574M Statistical Machine Learning
Computational Tools Certificate
CSC 501 Advanced Programming
BIOS 576E Data Management
CSC 544 Data Visualization
Students will apply their skills in a final, hands-on project that tackles a real-world problem. They will develop a professional-level analysis or tool that contributes to their professional portfolios and demonstrate their readiness for the workforce.
This course prepares students for the data science workplace by building both technical and career-readiness skills. Students will learn to create effective resumes and portfolios, write professional reports using tools like Markdown and Quarto, and manage projects with version control systems such as Git.
Stackable Certificates
MATH 509D: Statistics for Data Science
STAT 675: Statistical Computing
MATH 574M: Statistical Machine Learning
CSC 501: Advanced Programming
BIOS 576E: Data Management
CSC 544: Advanced Data Visualization
MCB 516A: Bioinformatics and Functional Genomic Analysis
MCB 547: Big Data in Molecular Biology and Biomedicine
MCB 580: Introduction to Systems Biology
ATMO 545: Introduction to Data Assimilation
HWRS 642: Analysis of Hydrologic Systems
HWRS 645: Computational Methods for Data Driven Earth Science