Search result: Catalogue data in Spring Semester 2021

GESS Science in Perspective Information
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.
851-0702-01LPublic Construction Law
Particularly suitable for students of D-BAUG
W2 credits2VO. Bucher
AbstractStudents will be introduced to the basic principles of planning and public construction legislation (development application procedures) as well as to the basics of public procurement law.
ObjectiveStudents shall have an understanding for the basic principles of planning and public construction legislation (incl. environmental law, development application procedures) as well as for the basics of public procurement law.
ContentTopics of this unit are: 1. Fundamentals of planning and public construction legislation (development, constitutional and legal foundation, basic principles and aims of spatial planning), 2. Federal, cantonal and communal planning legislation, 3. Public construction law (accessibility, zoning, construction and land use regulations [incl. environmental, water, heritage and energy use law], 4. Development application proceedings (obtaining development consent, appeal proceedings), 5. Basics of public procurement law
Lecture notesALAIN GRIFFEL, Raumplanungs- und Baurecht - in a nutshell, Dike Verlag, 3. A., Zürich 2017

CLAUDIA SCHNEIDER HEUSI, Vergaberecht - in a nutshell, Dike Verlag, 2. A., Zürich 2018

Die Vorlesung basiert auf diesen Lehrmitteln.
LiteraturePETER HÄNNI, Planungs-, Bau- und besonderes Umweltschutzrecht, 6. A., Bern 2016

WALTER HALLER/PETER KARLEN, Raumplanungs-, Bau- und Umweltrecht, Bd. I, 3. A., Zürich 1999
Prerequisites / NoticeVoraussetzungen: Vorlesung Rechtslehre GZ (851-0703-00/01)
851-0648-00LMachine Learning for Global Development Restricted registration - show details
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.
W3 credits2GJ. D. Wegner, L. Hensgen, A. Rom
AbstractIn 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.
ObjectiveThe 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.
ContentThis 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 / NoticeThis 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).
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