GEG 4120 Spatial Data Science

3 units
Geography
Faculty of Arts
Spatial data science is useful in many fields, including big data, population health sciences, biological sciences, earth sciences, medicine, engineering and social sciences. In this course, you will learn how to manipulate, analyze and model spatial data. Sections of the course focus on stochastic simulation and Monte Carlo methods in point-pattern analysis, spatial autocorrelation and geostatistics. Practical applications utilize the open-source software and data science computing languages (e.g. R, Python), no previous experience required. At the end of this course, you will have a toolbox of spatial analytical skills and a solid understanding of their appropriate applications to real-world questions.

Components:

Lecture

Requirements:

Prerequisites: GEG 2320 , GEG 3312 .

Previously Offered Terms:

Fall
Winter

French Equivalent:

Organized

20 responses

4.60

/ 5

strongly agree
70%
agree
25%
disagree
5%
strongly disagree
0%
25%
50%
75%
100%

Clear Expectations

14 responses

4.79

/ 5

strongly agree
86%
agree
7%
neither agree nor disagree
7%
disagree
0%
strongly disagree
0%
25%
50%
75%
100%

Learned a Lot

20 responses

4.80

/ 5

strongly agree
80%
agree
20%
disagree
0%
strongly disagree
0%
25%
50%
75%
100%

Recommend

6 responses

3.67

/ 5

strongly agree
33%
agree
33%
disagree
33%
strongly disagree
0%
25%
50%
75%
100%

Workload

6 responses

2.17

/ 5

very heavy
33%
heavier than average
17%
average
50%
lighter than average
0%
very light
0%
25%
50%
75%
100%

Fair Assessments

20 responses

4.65

/ 5

strongly agree
65%
agree
35%
disagree
0%
strongly disagree
0%
question not applicable
0%
25%
50%
75%
100%