Course 2025-2026 a.y.

The course is structured into three interconnected building blocks, each designed to progressively develop students’ understanding and practical skills in applying computational tools to climate change research.

1. Introduction to climate change study

This introductory module provides the essential conceptual foundation for understanding climate change as a global phenomenon with far-reaching social, economic, and political consequences. The emphasis is on the societal dimensions of climate change – how it is experienced, mediated, and addressed across different contexts and populations.

Key topics include:

- Overview of climate change drivers and impacts and projected global trends

- The role of population dynamics in shaping both vulnerability to and capacity for climate change mitigation and adaptation;

- Sector-specific impacts of climate change including health, human mobility and food security

- Climate justice and equity, including intergenerational, gender, and spatial disparities in climate risks and responsibilities

2. Introduction to databases and computational methods

This block provides a conceptual and practical introduction to key databases and computational approaches used in climate change research. It is divided into two parts:

2.1 Computational methods and tools

Students will receive an introduction to several data science tools, including hands-on lab sessions covering topics in machine learning and deep learning commonly used in climate-related research.

2.2 Critical reading of applied research

In this section, students will examine how computational methods are applied in climate change research through the critical reading of selected empirical studies. Working in groups, they will analyse key components of each study including the research questions, data sources, computational techniques used and key findings. One class will be specifically dedicated to providing an overview of data sources relevant to climate research including geo-referenced climate and environmental data and demographic, social and economic data.

3. Project work: designing and presenting a climate data-driven study

This final block focuses on a group-based research project. Students will work together to identify a relevant climate-related research question, design a data-driven approach, and apply computational methods to analyse the issue. Toward the end of the course, each group will present their project. In addition, every student will submit an individual written report reflecting their contribution and learning, which will be part of the overall assessment.

-          Explain the key concepts, drivers, and impacts of climate change, including climate scenarios, risk, vulnerability, adaptation, and mitigation.

-          Describe the societal dimensions of climate change, with attention to equity, justice, and population heterogeneity in climate impacts and responses.

-          Identify the types and sources of data commonly used in climate change research, including geo-referenced environmental data and demographic and socioeconomic data.

-          Understand the application of current computational tools and techniques in addressing climate change-related research questions

- Formulate a relevant research question related to climate change and design an appropriate, data-driven research plan.

- Locate, select, and manage relevant climate and social datasets for empirical analysis.

- Apply basic computational tools (e.g. machine learning algorithms, text mining, simulations) to analyse climate-related data and outcomes.

- Communicate scientific findings clearly and effectively, both orally and in written formats, using appropriate visualisations and reporting standards.

- Collaborate in teams to design and deliver a research projectü

Guest speaker’s talks

Invited experts to deliver focused talks on applications of computational tools in climate change research covering the topics in the first block “Introduction to climate change study”.

Exercises

Hands-on exercises using real datasets and computational tools relevant to climate and social data analysis. Students will use programming environments (e.g. Python or R) to work through guided coding exercises to be taken place in the second block “Introduction to databases and computational methods”

Interactive class activities

- Reading presentations: During the critical reading module, each group presents one study and leads class discussion on its strengths and limitations.

- Project presentations: At the end of the course, each group presents their final project in class, receiving feedback from instructors and peers.

Group assignments

Group work is central to two course components:

- Critical reading of applied research: students work in groups to analyze empirical studies, assess research design and methods, and present their findings in class.

- Group research project: students collaboratively design and implement a climate change-related study. This involves identifying a research question, selecting data, applying computational methods, and presenting the project.

Individual assignments

Each student is required to complete two individual written tasks:

- A research essay (3,500 words, excluding tables, figures, and references) presenting the group project’s research question, data, methodology, results, and interpretation in a coherent, scholarly format.

- An individual report (1,000 words) detailing the student’s specific contribution to the group project, their understanding of the methodological approaches used, and a critical reflection on the research process and teamwork experience.

• Oral individual exam

• Individual Works/ Assignment (report, exercise, presentation, project work etc.)

• Collaborative Works / Assignment (report, exercise, presentation, project work etc.)

• Active class participation (virtual, attendance)

The partial exams are open exclusively to students who attend the lectures regularly.

Individual assignment (partial exam): 50% of the grade

Group assignment (partial exam): 40% of the grade

Participation (continuous assessment): 10% of the grade

Participation involves attending lectures and engaging in class discussion. 

The general exams apply to non-attending students.

Individual assignment (general exam): 60% of the grade

Oral exams (general exam): 40% of the grade

There is no textbook for this course.

Each lecture revolves around a couple of academic papers and scientific findings. Relevant papers and book chapters are made available via the Bocconi e-learning platform.

Students who need extra background  can consult the following books:

Brechin, S. R., & Lee, S. (2025). Routledge Handbook of Climate Change and Society. Abingdon New York (N.Y.): Routledge.

Hunter, L. M., Gray, C., & Véron, J. (Eds.). (2022). International Handbook of Population and Environment. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-76433-3_1