Schedule

Here’s your roadmap for the semester!

  • Content (): This page contains the readings, slides, and recorded lectures for the week. Read the various readings before our scheduled class time.

  • Lesson (): This page contains a tutorial video and additional annotated R code and other supplementary information that you can use to help you prepare for the in-class exercises and assignments. These are most helpful if you watch them before in-class sessions so that you can ask questions when we start working through things together.

  • Exercises (): This page the scripts that we work on in class as a reminder of some of the live-coding exercises. These are provided as a reference to help you link your notes to the syntax we use in class.

  • Assignment (): This page contains the instructions for each assignment. Assignments are due by 11:59 PM on the day they’re listed. One more time!

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Getting Started

Title Content Lesson Exercises Assignment
August 25
(Session 1) 		Introduction to the Course
August 27
(Session 2) 		Tools of the Trade
August 29  Self-Evaluation 1 due  (submit by 11:59 PM)
September 1 No Class
(Labor Day)
September 3
(Session 4) 		Meeting Your data
September 8
(Session 5) 		Data Manipulation with the tidyverse
September 10
(Session 6) 		Pipes, Functions, and Iteration
September 11  Homework 1

Fundamentals of Spatial Data

Title Content Lesson Exercises Assignment
September 15
(Session 7) 		Data Models, Coordinates, and Geometries
September 17
(Session 8) 		Projections, Ectent, and Resolution
September 18  Homework 1 Revision
September 22
(Session 9) 		Attribute Data Operations
September 24
(Session 10) 		Spatial Data Operations
September 29
(Session 11) 		Geometry Data Operations and Troubleshooting
October 1
(Session 12) 		Building Spatial Databases
October 1  Final Project Contract Due
October 2  Homework 2

Describing Spatial Patterns

Title Content Lesson Exercises Assignment
October 6
(Session 13) 		Point Patterns I
October 8
(Session 14) 		Point Patterns II
(remote)
October 9  Homework 2 Revision
October 13
(Session 15) 		Surface Metrics I
October 15
(Session 16) 		Surface Metrics II
October 20
(Session 17) 		Multivariate Description I
October 22
(Session 18) 		Multivariate Description II
October 23  Homework 3

Explaining Spatial Patterns

Title Content Lesson Exercises Assignment
October 27
(Session 19) 		Interpolation
October 29
(Session 20) 		Kriging
October 30  Homework 3 Revision
November 1  Final Project Description Due
November 3
(Session 21) 		Machine Learning Models I
November 5
(Session 22) 		Machine Learning Models II
November 10
(Session 23) 		Statistical Modelling I
November 12
(Session 24) 		Statistical Modelling II
November 17
(Session 25) 		Spatial Autocorrelation I
November 19
(Session 26) 		Spatial Autocorrelation II
November 20  Homework 4

Fall Break

Title Content Lesson Exercises Assignment
November 24 No Class
(Fall Break)
November 26 No Class
(Fall Break)

Predicting Spatial Patterns

Title Content Lesson Exercises Assignment
December 1
(Session 29) 		Spatial Predictions
December 2  Homework 4 Revision
December 3
(Session 30) 		Model Evaluation I
December 8
(Session 31) 		Model Evaluation II
December 9  Homework 5

Wrapup

Title Content Lesson Exercises Assignment
December 9  Draft Final Project Due  (submit by 11:59 PM)
December 10
(Session 32) 		Conclusion
December 11  Homework 5 Revision
December 12 Final Project Workday
(optional)
December 18  Final Project Due  (submit by 11:59 PM)
December 19  Final Self-Evaluation Due  (submit by 11:59 PM)