Search result: Catalogue data in Spring Semester 2021
|GESS Science in Perspective
Only the courses listed below will be recognized as "GESS Science in Perspective" courses.
Further below you will find courses under the category "Type B courses Reflections about subject specific methods and content" as well as the language courses.
During the Bachelor’s degree Students should acquire at least 6 ECTS and during the Master’s degree 2 ECTS.
Students who already took a course within their main study program are NOT allowed to take the course again.
| Type B: Reflection About Subject-Specific Methods and Contents
Subject-specific courses: Recommended for bachelor students after their first-year examination and for all master- or doctoral students.
Students who already took a course within their main study program are NOT allowed to take the same course again.
All these courses are listed under the category “Typ A”, this means, every student can enroll in these courses.
|Supply and Responsible Use of Mineral Resources I
|B. Wehrli, F. Brugger, K. Dolejs Schlöglova, M. Haupt, C. Karydas
|Students critically assess the economic, social, political, and environmental implications of extracting and using energy resources, metals, and bulk materials along the mineral resource cycle for society. They explore various decision-making tools that support policies and guidelines pertaining to mineral resources, and gain insight into different perspectives from government, industry, and NGOs.
|Students will be able to:
- Explain basic concepts applied in resource economics, economic geology, extraction, processing and recycling technologies, environmental and health impact assessments, resource governance, and secondary materials.
- Evaluate the policies and guidelines pertaining to mineral resource extraction.
- Examine decision-making tools for mineral resource related projects.
- Engage constructively with key actors from governmental organizations, mining and trading companies, and NGOs, dealing with issues along the mineral resource cycle.
|Prerequisites / Notice
|Bachelor of Science, Architecture or Engineering, and enrolled in a Master's or PhD program at ETH Zurich. Students must be enrolled in this course in order to participate in the case study module course 860-0016-00 Supply and Responsible Use of Mineral Resources II.
|Supply and Responsible Use of Mineral Resources II
Number of participants limited to 12.
First priority will be given to students enrolled in the Master of Science, Technology, and Policy Program. These students must confirm their participation by 12.02.2021 by registration through myStudies. Students on the waiting list will be notified at the start of the semester.
Prerequisite is 860-0015-00 Supply and Responsible Use of Mineral Resources I.
|B. Wehrli, F. Brugger, S. Pfister
|Students integrate their knowledge of mineral resources and technical skills to frame and investigate a commodity-specific challenge faced by countries involved in resource extraction. By own research they evaluate possible policy-relevant solutions, engaging in interdisciplinary teams coached by tutors and experts from natural social and engineering sciences.
|Students will be able to:
- Integrate, and extend by own research, their knowledge of mineral resources from course 860-0015-00, in a solution-oriented team with mixed expertise
- Apply their problem solving, and analytical skills to critically assess, and define a complex, real-world mineral resource problem, and propose possible solutions.
- Summarize and synthesize published literature and expert knowledge, evaluate decision-making tools, and policies applied to mineral resources.
- Document and communicate the findings in concise group presentations and a report.
|Prerequisites / Notice
|Prerequisite is 860-0015-00 Supply and Responsible Use of Mineral Resources I. Limited to 12 participants. First priority will be given to students enrolled in the Master of Science, Technology, and Policy Program. These students must confirm their participation by February 7th by registration through MyStudies. Students on the waiting list will be notified at the start of the semester.
|Ecology and Environmentalism
Number of participants limited to 40
Particularly suitable for students of D-ERDW, D-HEST, D-USYS, D-BIOL
|The notion of „ecology“ refers to both, scientific research on environments as well as their protection. But how have academic ecology and the environmental movements intersected throughout history?
|In the seminar, students will read and discuss key sources as well as secondary literature on the knowledge transfers between scientific ecology and the environmental movements of the 19th and 20th century. Topics range from 19th-century homeland movement and the rise of ecological awareness in colonial settings, to the rise of an environmental awareness during the Cold War, with a special focus on „green“ politics in Europe. Apart from scientists and „counter-scientists“ the seminar focuses on concepts and ideas that circulated between academic ecology and different nature movements.
The participants learn to engage historically with original texts as well as to handle independently the extensive historical literature on the history of environmentalism. At the same time, they develop a critical understanding of different political agendas that have shaped academic and popular ecology until the present day. Students also learn to communicate their findings by writing short (and fictive) blog posts on different aspects of this history.
|Machine Learning for Global Development
Number of participants limited to 24
Prerequisite: Students on BSc or MSc level who have already successfully participated in a data science and programming course.
|J. D. Wegner, L. Hensgen, A. Rom
|In this course students will learn theories of machine learning and its application to problems in the context of global development, with a focus on developing countries (e.g. predicting the risk of child labor or chances of a malaria outbreak). By the end of the course, students will be able to critically reflect upon linkages between technical innovations, culture and individual/societal needs.
|The objective of this course is to introduce students with a non-technical background to machine learning. Emphasis is on hands-on programming and implementation of basic machine learning concepts to demystify the subject, equip participants with all necessary insights and tools to develop their own solutions, and to come up with original ideas for problems related to the context of global development. Specific importance is placed upon the reconciliation of the predictions, which have been generated by automated processes, with the realities on the ground; hence the linkage between technical and social issues. This raises questions such as “In how far can we trust an algorithm?”, “Which factors are hard to measure and therefore not integrated in the algorithm but still crucial for the result, such as cultural and social influences?”. These questions will be discussed in the interdisciplinary group, equipping students with various perspectives on this crucial and very current debate.
|This course will give an introduction to machine learning with emphasis on global development. We will discuss topics like data preprocessing, feature extraction, clustering, regression, classification and take some first steps towards modern deep learning. The course will consist of 50% lectures and 50% hands-on programming in python, where students will directly implement learned theory as a software to help solving problems in global development.
|Prerequisites / Notice
|This course will give an introduction to machine learning with emphasis on applications in global development. It will consist of 50% lectures and 50% programming exercises (in python). Teaching assistants from the EcoVision Lab will help with all programming exercises without any needs for additional funding.
Students should bring their laptops to the exercises because we will program on laptops directly.
It is required that students enrolling in this course have successfully passed a course that deals with basic data science and are familiar with programming (preferably in Python).
|What Is Knowledge and Under What Conditions Are We Entitled to Claim Knowledge?
|The seminar aims at a clarification of the concept of knowledge, as it is built in our experiential relations to the world. An analysis is needed of the difference between knowledge and belief, of the relation between objectivity and knowledge, and of the role of reasons for having knowledge. Additionally, the legitimacy of different types of knowledge claims should be evaluated.
|On will able to evaluate the arguments pro and con the thesis, that knowledge is justified, true belief. Furthermore, one will gain some insights in the role of reasons for knowledge and in the merits and misgivings of a naturalistic account of knowledge. Finally, one will be a bit more familiar with some theories of philosophical epistemology (e.g. empiricism, rationalism).
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