Date Week Day Topic Due Readings
15-May 1 1 Introduction to course    
16-May 1 2 Introduction to R   R For Data Science, Chapters 1.1-1.6, Working Directory, File Paths Help document (in helpful docs)
17-May 1 3 In Class Activity   Introduction to RMarkdown (in helpful docs)
20-May 2 4 Introduction to Tidyverse   Tidy Data
21-May 2 5 In Class Activity- Tidyverse vs. Base R, Work on HW1 HW 1 Tidyverse Skeptic, Teaching Tidyverse to Beginnners
22-May 2 6 Spatial Data Day 1   Basic Data Types, Coordinate Systems, Feature Representation
23-May 2 7 Spatial Data Day 2    
24-May 2 8 Mapping   Tmap in a Nutshell, Introduction to Tmap(in helpful docs)
28-May 3 9 Mapping In Class Activity    
29-May 3 10 Data Wrangling HW 2 Data Manipulation with dplyr
30-May 3 11 Exam 1, Introduction to Project    
31-May 3 12 Asking Spatial Questions, Filter and Aggregate, Join Project Task 1 Data Wrangling in R
3-Jun 4 13 Exploratory Spatial Data Analysis    
4-Jun 4 14 Computational Thinking, Control Structures, and Functions HW 3 Control Structures, Functions
5-Jun 4 15 In Class Activity- Control Structures + Functions Project Task 2  
6-Jun 4 16 Geographic Fundamentals    
7-Jun 4 17 Exam 2 HW 4  
10-Jun 5 18 Spatial Data Analysis   GIS Analysis Toolkit
11-Jun 5 19 In Class Activity - GIS Project Task 3  
12-Jun 5 20 Calculating Distance Spatial Neighbors    
13-Jun 5 21 Spatial Clustering   Global Spatial Autocorrelation, Local Spatial Autocorrelation
14-Jun 5 22 Bivariate Relationships HW 5  
17-Jun 5 23 Spatial Regressions   Spatial Regressions
18-Jun 6 24 Catch-up/ Project Workday    
21-Jun 6 25 Exam Period, 8:00-11:00am