Syllabus

Fall Semester • ETH Zurich
Thursdays • Sep 17–Dec 17 • 08:15–10:00 and 18:15–20:00

This course uses an active-classroom format built around hands-on practice, discussion, and collaboration. Most morning sessions pair a 45-minute methods deep-dive with 45 minutes of collaborative work on module projects. Most evening sessions pair a 45-minute critical reflection on the readings with 45 minutes of collaborative project work.

Schedule note: The schedule may change as the course progresses because some content may warrant more time. Any updates will be posted here.

Date Morning (8:15–10a) Evening (6:15–8p) Readings
Sep 17 Course introduction · 45 minHow data science plays a role throughout the environmental policy cycleTech setup · 45 minGitHub, VS Code or Codespaces, and an introduction to coding in R Not all models are created equalLLM assistance in class (local vs hosted) and designing a collective code of conductCourse setupReproducible workflowsStep-by-step setup (class activity) Tech Setup
Module 1 Sep 24 Module introductionThe politics of planetary scale dataMethods deep-diveIntroduction to spatial data and analysis, getting started on Module 1Start your Module 1 repository (class activity)Module 1 template on GitHub Critical reflection · 30 minA Political Ecology of DataHow do the infrastructures, institutions, and practices that produce environmental data shape what can be known, governed, and contested?Module projectPair programming: Module 1Collaboration skill: resolving a Git merge conflict A Political Ecology of Data (Nost & Goldstein, 2022)Optional module prep:Biodiversity data disparities (Chapman et al., 2024)
Oct 1 Methods deep-dive · 45 minCloud-native geospatial workflows, efficient data storage and accessWeek 3 slides: Cloud-native data in RModule project · 45 minPair programming: Module 1 Critical reflection · 45 minInternet PowerRole-play negotiation: who hosts, pays for, and sets the method for a billion-dollar climate disaster database?Discussion intro slidesModule project · 45 minPair programming: Module 1 Internet Power
STAC Spec
Oct 8 Module 1 presentations · 45 minModule 1 findingsEach group gives a three-minute presentation on its findingsTA presentations · 45 minData science in environmental researchHear how the TAs use data science in their PhD research Final project introductionStructured brainstorming for final projectsForm groups and brainstorm ideas with support from the teaching staffFinal project brainstorm slides —Due date: Module 1 reflection
Module 2 Oct 15 Module introductionFrom structured to unstructured data: policy documents and public discourseCritical reflection · 45 minDigital technology refusal in environmental movements Module projectPeer programming: Module 2 Large Language Models in public policy research (Lan et al., 2026)
Oct 22 Guest lectureClimate policy discourse analysisGuest lecturer: Tobias Schimanski Guest tutorialClimate policy discourse analysisGuest lecturer: Tobias Schimanski To Disclose, or Not to Disclose: Evaluating the Effectiveness of Mandatory Climate-Related Disclosure
What Firms Actually Lose (and Gain) from Extreme Weather Event ImpactsFor both papers, focus especially on the NLP/LLM sections.
Module 3 Oct 29 Module introduction · 45 minFrom data to decisions: The promise and perils of algorithmic environmental governanceMethods deep-dive · 45 minSpatial optimization for land-use planning Critical reflection · 45 minHow values change algorithmic outputsModule project · 45 minPeer programming: Module 3 Social considerations for the 30×30 conservation target (Sandbrook et al., 2023)
prioritizr workshop manual (Hanson & Schuster, 2023)Due date: Module 2 reflection
Nov 5 Methods deep-dive · 45 minAdaptive and dynamic decision-making algorithmsModule project · 45 minPeer programming: Module 3 Critical reflection · 45 minAccountability, power and participation in algorithmic environmental governanceModule project · 45 minPeer programming: Module 3 Geographies of conservation II: Technology, surveillance and conservation by algorithm (Adams, 2019)
Nov 12 Module 3 presentations · 45 minModule 3 findingsEach group gives a five-minute presentation on its findings Final project proposalCoworking and peer consultationDevelop project ideas and exchange feedback with peers and teaching staff —Due date: Module 3 reflection
Module 4 Nov 19 Module introduction · 45 minFrom intervention to impact: causal inference for evaluating environmental policyModule project · 45 minPeer programming: Module 4 Critical discussion · 45 minChallenges of equitably assessing policy impactModule project · 45 minPeer programming: Module 4 TBDDue date: Final project proposal
Nov 26 Methods deep-dive · 45 minDifference-in-differences, event studies, and matched designsModule project · 45 minPeer programming: Module 4 Module projectPeer programming: Module 4 TBD
Module 5 Dec 3 Data-driven reflectionThe environmental costs of compute Final projectCoworking and consultationDevelop your project with support from peers and teaching staff TBDDue date: Module 4 reflection
Dec 10 Final project · 45 minCoworking sessionProfessional development · Optional workshop · 45 minWebsite design Final projectCoworking session —
Dec 17 Final projectPresentations Class reflections —Due date: Final project

Module deliverables and reflections

Modules 1 and 3, as well as Module 5 (the final project), have presentation-based deliverables and short written reflections. Modules 2 and 4 have written reflections only.

Expectations for reflections:

  1. Share a GitHub repository with the teaching staff that demonstrates your engagement with the module content.
  2. Choose a figure from your module output and explain how you calculated it, how you interpret it, and what limitations or considerations should inform that interpretation.
  3. Write a short, one-paragraph reflection on one technical insight and one critical insight you gained through the module.