Professional Applications of Data Science Graduate Academic Certificate
All required coursework must be completed with a grade of B or better (O-10-b).
| Code | Title | Hours |
|---|---|---|
| INTR 509 | Introduction to Applied Data Science | 3 |
| BCB 521 | Communicating with Data | 2 |
| BCB 520 | Foundations of Data Visualization | 3 |
| BCB 522 | Data Science Portfolio | 1 |
| Electives (Choose one of the following) 1 | 3 | |
| Practical Methods in Analyzying Animal Science Experiments | ||
| Image Processing and Computer Vision | ||
| Systems Biology | ||
| Phylogenetics | ||
| Instrumentation and Measurements | ||
| Computer Skills for Biologists | ||
| Mathematical Genetics | ||
| Aquatic Habitat Modeling | ||
| Parallel Programming | ||
| Computational Biology: Sequence Analysis | ||
| Digital Forensics | ||
| Artificial Intelligence | ||
| Deep Learning | ||
| Machine Learning | ||
| Python for Machine Learning | ||
| Introduction to Quantitative Research | ||
| Evolutionary Computation | ||
| Neural Network Design | ||
| Data Science | ||
| Semantic Web and Open Data | ||
| Spatial Analysis and Modeling | ||
| Remote Sensing/GIS Image Analysis | ||
| Stochastic Models | ||
| Data Management for Big Data | ||
| Statistical Analysis | ||
| Nonparametric Statistics | ||
| Applied Regression Modeling | ||
| Statistical Learning and Predictive Modeling | ||
| Multivariate Analysis | ||
| Introduction to Bayesian Statistics | ||
| Statistical Ecology | ||
| Computer Intensive Statistics | ||
| Univariate Quantitative Research in Education | ||
| Multivariate Quantitative Analysis in Education | ||
| Theoretical Applications and Designs of Qualitative Research | ||
| Data Analysis and Interpretation of Qualitative Research | ||
| Indigenous and Decolonizing Research Methods | ||
| Decolonizing, Indigenous, and Action-Based Research Methods | ||
| Survey Design for Social Science Research | ||
| Methods of Educational Research | ||
| Research Methods for Local Government and Community Administration | ||
| Data Wizardry in Environmental Sciences | ||
| Research Methods in the Environmental Social Sciences | ||
| Forest Biometrics | ||
| Remote Sensing of Fire | ||
| LIDAR and Optical Remote Sensing Analysis | ||
| Landscape and Habitat Dynamics | ||
| Ecological Modeling | ||
| Statistical Ecology | ||
| Water Economics and Policy Analysis | ||
| Total Hours | 12 | |
- 1
Students should work with their advisors for potential substitution waivers.
Courses to total 12 credits for this certificate
Student Learning Outcomes
Upon completion of the certificate, students will be able to:
- Use open-source software to reproducibly manage, analyze, and visualize large, complex, and noisy data sets.
- Practice high quality and ethical data stewardship.
- Understand and execute data exploration.
- Effectively communicate data driven insights to experts and non-experts.
- Demonstrate their skills with an online portfolio of analyses and visualizations relevant to their field of specialization.