The DSTP is a 9-month program designed to teach USDA staff data science skills in Python and R. Participants learn concrete data science skills through a mix of virtual self-paced learning and live instruction. Participants work on USDA-relevant assignments (hosted in this repository) as well as customized learning tracks (70+ hours) in the virtual learning platform DataCamp. In addition to R and Python, particpants are taught how to use Git and EDAPT.
This repository houses my assignments completed as part of the DSTP. The program also included a capstone project, which is hosted under the GEE-Burn-Severity-Classification repository.
I completed the intermediate python track within the DSTP. As part of this track, I completed assignments and courses related to:
- Manipulating Data
- Summary Statistics
- Data Analysis
- Data Visualization
- Correlation Analysis
- Predictive Modeling
- Geographic Mapping
- Machine Learning