NRES 604 - Environmental Sensors and Data Science

(3 units)

Technology has driven rapid advancements in environmental sensing, but data science applications require careful field experiments and data management. Developing effective environmental monitoring requires knowledge across a variety of disciplines: field methods, electronics, computer programming, time series analysis, machine learning, and physical modelling. In this course, students will develop skills in these fields through hands-on activities and projects.

Maximum units a student may earn: 3

Grading Basis: Graded
Units of Lecture: 2
Units of Laboratory/Studio: 1
Offered: Every Fall

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. deploy an environmental sensor system by choosing sensors, programming dataloggers, estimating power needs, and understanding basic electronics in a hands-on setting.
2. create a quality assurance plan and quality control procedures for their sensor system or existing public dataset.
3. create a data management plan, associated metadata, and release the data in a public format using data their own data or a public dataset.
4. analyze existing time series data, improve its quality, and apply it in a model to make predictions using lab assignments and a class project.
5. apply time series analysis and other data science tools to an independent dataset to test a research hypothesis using lab assignments and a class project.

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