Online Spatial Data Handling

This course introduces geospatial standards and data formats commonly found on the web. Through a combination of lectures and hands on exercises using Jupyter Notebooks, students will learn to explore, query and perform spatial operations on geospatial data (e.g.: point pattern analysis, linear and logistic regression), while developing Notebooks that can be shared and re-used.

Note: This course requires you to install free, open-source software in order to complete the assignments. The software to be downloaded is Anaconda or Miniconda (which will install Python and Jupyter notebooks) and is compatible with Windows, MacOS, and Linux. More information will be given once you have been registered.

Instructor: Heather McGrath (please contact the instructor if you need an up-to-date syllabus)
Prerequisite: None. This course is the undergraduate level version of GGE 6404. Credit will not be given for both GGE 5404 and GGE 6404.

Why take this course?

• You will explore the benefits/use of a variety of geospatial standards and data formats.
• You will learn how to design and implement a pipeline of automated geospatial data operations and statistical analysis on geospatial data within a computational notebook that can be shared and re-used.
• By the end of the course, you will be able to identify and describe core concepts of cloud computing and computational notebooks.

Course details

Students have six months from the registration date to complete the course. All course exams and/or assignments must be completed by the designated end date.

Assignments and examinations

• 5 x Quizzes (25% total)
• 1 x Midcourse Test (20% total)
• 3 x Assignments (30% total)
• 1 x Final Exam (invigilated, 25% total)

Fees and payments

There is a $150 non-refundable/non-transferable online fee per course in addition to applicable tuition & fees. Learn more about tuition and fees and methods of payment.