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Data Science Programming in R and Python Syllabus
End of semester grade request letter
Class slides
D1: Introduction
D2: Technology
P1D1: Workflow and Github
P1D2: Visualization and the Tidyverse
P1D3: R programming wrap up
P1D4: Python for data science
P1D5: No class
P1D6: Open programming time for Python
P2D1: Getting data and gun deaths
P2D2: Functions and automation
P2D3: Open programming time
P2D4: Being and data scientist
P2D5: Writing Python code
P2D6: Open programming time
P3D1: Spatiotemporal Data
P3D2: Visualizing space and time
P3D3: Programming with spatial data
P3D4: Programming with spatial data (part 2)
P3D5: Visualizing Space and Time
P3D6: Ethics in modeling and scraping
P3D7: Open programming time (R)
P3D8: Coding challenge
P3D9: Programming with spatial data (Python)
P3D10: Spatial Calculations and Manipulations with GeoPandas
P3D11: Managing spatial and nested data in Python
P5D1: We don’t have time for the SQL
P4D1: Understanding the Pavlov in Machine Learning
P4D2: Cleaning data for scikit-learn and machine learning
P4D3: From scikit-learn to DALEX/SHAP
P4D3: From the Tidyverse to Tidymodels
P4D4: Model Explainers R
Readings
User Guides
VScode for Data Science
Slack
Github and Git
Packages in R and Python
Altair Visualization
Links to resources
Office Hours
User Guides
Short guides for our course (as needed).
Table of contents
VScode for Data Science
Slack
Github and Git
Packages in R and Python
Altair Visualization
Links to resources