Suchergebnis: Katalogdaten im Herbstsemester 2017

Informatik Bachelor Information
Bachelor-Studium (Studienreglement 2016)
227-0945-00LCell and Molecular Biology for Engineers I
This course is part I of a two-semester course.
W3 KP3GC. Frei
KurzbeschreibungThe course gives an introduction into cellular and molecular biology, specifically for students with a background in engineering. The focus will be on the basic organization of eukaryotic cells, molecular mechanisms and cellular functions. Textbook knowledge will be combined with results from recent research and technological innovations in biology.
LernzielAfter completing this course, engineering students will be able to apply their previous training in the quantitative and physical sciences to modern biology. Students will also learn the principles how biological models are established, and how these models can be tested.
InhaltLectures will include the following topics: DNA, chromosomes, RNA, protein, genetics, gene expression, membrane structure and function, vesicular traffic, cellular communication, energy conversion, cytoskeleton, cell cycle, cellular growth, apoptosis, autophagy, cancer, development and stem cells.

In addition, three journal clubs will be held, where one/two publictions will be discussed (part I: 1 Journal club, part II: 2 Journal Clubs). For each journal club, students (alone or in groups of up to three students) have to write a summary and discussion of the publication. These written documents will be graded and count as 25% for the final grade.
SkriptScripts of all lectures will be available.
Literatur"Molecular Biology of the Cell" (6th edition) by Alberts, Johnson, Lewis, Raff, Roberts, and Walter.
351-0778-00LDiscovering Management
Entry level course in management for BSc, MSc and PHD students at all levels not belonging to D-MTEC. This course can be complemented with Discovering Management (Excercises) 351-0778-01.
W3 KP3GB. Clarysse, M. Ambühl, S. Brusoni, E. Fleisch, G. Grote, V. Hoffmann, T. Netland, G. von Krogh, F. von Wangenheim
KurzbeschreibungDiscovering Management offers an introduction to the field of business management and entrepreneurship for engineers and natural scientists. The module provides an overview of the principles of management, teaches knowledge about management that is highly complementary to the students' technical knowledge, and provides a basis for advancing the knowledge of the various subjects offered at D-MTEC.
LernzielDiscovering Management combines in an innovate format a set of lectures and an advanced business game. The learning model for Discovering Management involves 'learning by doing'. The objective is to introduce the students to the relevant topics of the management literature and give them a good introduction in entrepreneurship topics too. The course is a series of lectures on the topics of strategy, innovation, corporate finance, leadership, design thinking and corporate social responsibility. While the 14 different lectures provide the theoretical and conceptual foundations, the experiential learning outcomes result from the interactive business game. The purpose of the business game is to analyse the innovative needs of a large multinational company and develop a business case for the company to grow. This business case is as relevant to someone exploring innovation within an organisation as it is if you are planning to start your own business. By discovering the key aspects of entrepreneurial management, the purpose of the course is to advance students' understanding of factors driving innovation, entrepreneurship, and company success.
InhaltDiscovering Management aims to broaden the students' understanding of the principles of business management, emphasizing the interdependence of various topics in the development and management of a firm. The lectures introduce students not only to topics relevant for managing large corporations, but also touch upon the different aspects of starting up your own venture. The lectures will be presented by the respective area specialists at D-MTEC.
The course broadens the view and understanding of technology by linking it with its commercial applications and with society. The lectures are designed to introduce students to topics related to strategy, corporate innovation, leadership, corporate and entrepreneurial finance, value chain analysis, corporate social responsibility, and business model innovation. Practical examples from industry experts will stimulate the students to critically assess these issues. Creative skills will be trained by the business game exercise, a participant-centered learning activity, which provides students with the opportunity to place themselves in the role of Chief Innovation Officer of a large multinational company. As they learn more about the specific case and identify the challenge they are faced with, the students will have to develop an innovative business case for this multinational corporation. Doing so, this exercise will provide an insight into the context of managerial problem-solving and corporate innovation, and enhance the students' appreciation for the complex tasks companies and managers deal with. The business game presents a realistic model of a company and provides a valuable learning platform to integrate the increasingly important development of the skills and competences required to identify entrepreneurial opportunities, analyse the future business environment and successfully respond to it by taking systematic decisions, e.g. critical assessment of technological possibilities.
Voraussetzungen / BesonderesDiscovering Management is designed to suit the needs and expectations of Bachelor students at all levels as well as Master and PhD students not belonging to D-MTEC. By providing an overview of Business Management, this course is an ideal enrichment of the standard curriculum at ETH Zurich.
No prior knowledge of business or economics is required to successfully complete this course.
363-0511-00LManagerial Economics
Not for MSc students belonging to D-MTEC!
W4 KP3VS. Rausch, V. Hoffmann
KurzbeschreibungManagerial Economics beschäftigt sich mit der Anwendung ökonomischer Theorien und Methoden auf die Probleme der Entscheidungen von Marktakteuren. Der Kurs behandelt ökonomische Konzepte der Optimierung, der Konsumententheorie, der Theorie der Firma, der Industrieökonomik und der Entscheidungsfindung unter Unsicherheit. Theoretische Aspekte werden anhand von angewandten Methoden aus der numerische
LernzielDer Kurs bietet sowohl Bachelor als auch Master und PhD Studenten in MAVT eine Einführung in die Anwendung ökonomischer Konzepte für die Lösung von Managemententscheidungsproblem innerhalb einer Firma. Neben der Beschäftigung mit relevanten ökonomischen Theorien, sollen Studenten angewandten Methoden aus der numerischen Analyse, Statistik, Spieltheorie und Optimierung erlernen. Der Kurs beinhalt drei Vorlesungen von Professor Hoffmann, die sich auf relevante Management-Fallstudien konzentrieren.
LiteraturMikroökonomie (Pearson Studium - Economic VWL) Gebundene Ausgabe, August 2013, Robert S. Pindyck, Dr. Daniel L. Rubinfeld.
Voraussetzungen / BesonderesDer Kurs richtet sich sowohl an Bachelor als auch Master und PhD Studenten und bietet eine Einführung in die ökonomischen Konzepte und quantitativen Methoden, die für die Lösung von Managemententscheidungsproblemen von Relevanz sind. Für eine erfolgreiche Belegung des Kurses ist kein spezielles Vorwissen im den Bereichen Ökonomik und Management erforderlich.
363-0585-00LIntermediate EconometricsW3 KP2VM. Kesina
KurzbeschreibungThe idea of this course is to familiarize students with instrumental variables estimation of linear regression models and the estimation of models with limited dependent variables as well as of nonlinear regression models. While most of the material covered will pertain to cross-sectional data, we will also work on selected issues with panel data.
LernzielI will provide STATA programs and show the execution thereof. After having participated in this course, students will be able to carry out simple research projects and understand the basics of intermediate econometrics. In particular, they will be able to write simple programs in STATA and to qualify their own and others' regression output relating to problems covered.
LiteraturJeffrey M. Wooldridge: Introductory Econometrics; Jeffrey M. Wooldridge: Econometric Analysis of Cross Section and Panel Data; A. Colin Cameron and Pravin K. Trivedi. Microeconometrics: Methods and Applications.
363-1047-00LEconomics of Urban TransportationW3 KP2GA. Russo
KurzbeschreibungThe first part of the course will present some basic principles of transportation economics, applied to the main issues in urban transport policy (e.g. road pricing, public transport tariffs, investment in infrastructure etc.). The second part of the course will consider some case studies where we will apply the tools acquired in the first part to actual policy issues.
LernzielThe main objective of this course is to provide students with some basic tools to analyze transport policy decisions from an economic perspective. Can economics help us reduce road congestion problems? Should drivers be asked to pay for using urban roads? Should public transport tariffs depend on how roads are priced? How should the investment in transport infrastructure be financed? These are some of the questions that students should be able to tackle after completing the course.
InhaltCOURSE OUTLINE (preliminary):

1. Introduction
2. Travel demand :
a. travel cost and value of time
b. mode choice
3. Road congestion and first-best pricing
a. Static congestion model
b. Dynamic congestion models
c. Examples: London Congestion Charge, Stockholm Congestion Charge
4. Second-best pricing
a. Pricing roads with unpriced alternatives. Examples: tolled and toll-free highways
b. Public transport: pricing with road congestion and with (or without) road tolls
5. Investment in infrastructure: public transport and roads
a. Roads: Investment with and without pricing
b. induced demand
c. Economies of scale/density in public transport
6. Topics:
a. Political economy of road pricing: why do we see road pricing in so few cities (London, Stockholm...) and not in many other cities (NYC, Manchester, Paris...)?
b. What are the alternatives to road pricing to reduce congestion? Parking tariffs, traffic regulation (speed bumps, low emission zones), road space reduction. Examples: Zurich, San Francisco (SFPark), Paris.
c. Transport and land use: value of housing and transport services. Road congestion, transport subsidies and urban sprawl.
SkriptCourse slides will be made available to students prior to each class.
LiteraturSYLLABUS (preliminary):

course slides will be made available to students.

Additional material:

Part 1 to 5: textbook: Small and Verhoef (The economics of urban transportation, 2007).

Part 6: Topics to be covered on research papers/case studies.
376-1177-00LHuman Factors IW3 KP2VM. Menozzi Jäckli, R. Huang, M. Siegrist
KurzbeschreibungEvery day humans interact with various systems. Strategies of interaction, individual needs, physical & mental abilities, and system properties are important factors in controlling the quality and performance in interaction processes. In the lecture, factors are investigated by basic scientific approaches. Discussed topics are important for optimizing people's satisfaction & overall performance.
LernzielThe goal of the lecture is to empower students in better understanding the applied theories, principles, and methods in various applications. Students are expected to learn about how to enable an efficient and qualitatively high standing interaction between human and the environment, considering costs, benefits, health, and safety as well. Thus, an ergonomic design and evaluation process of products, tasks, and environments may be promoted in different disciplines. The goal is achieved in addressing a broad variety of topics and embedding the discussion in macroscopic factors such as the behavior of consumers and objectives of economy.
Inhalt- Physiological, physical, and cognitive factors in sensation and perception
- Body spaces and functional anthropometry, Digital Human Models
- Experimental techniques in assessing human performance and well-being
- Human factors and ergonomics in system designs, product development and innovation
- Human information processing and biological cybernetics
- Interaction among consumers, environments, behavior, and tasks
Literatur- Gavriel Salvendy, Handbook of Human Factors and Ergonomics, 4th edition (2012), is available on NEBIS as electronic version and for free to ETH students
- Further textbooks are introduced in the lecture
- Brouchures, checklists, key articles etc. are uploaded in ILIAS
401-7855-00LComputational Astrophysics (University of Zurich)
Der Kurs muss direkt an der UZH belegt werden.
UZH Modulkürzel: AST245

Beachten Sie die Einschreibungstermine an der UZH:
W6 KP2VL. M. Mayer
LernzielAcquire knowledge of main methodologies for computer-based models of astrophysical systems,the physical equations behind them, and train such knowledge with simple examples of computer programmes
Inhalt1. Integration of ODE, Hamiltonians and Symplectic integration techniques, time adaptivity, time reversibility
2. Large-N gravity calculation, collisionless N-body systems and their simulation
3. Fast Fourier Transform and spectral methods in general
4. Eulerian Hydrodynamics: Upwinding, Riemann solvers, Limiters
5. Lagrangian Hydrodynamics: The SPH method
6. Resolution and instabilities in Hydrodynamics
7. Initial Conditions: Cosmological Simulations and Astrophysical Disks
8. Physical Approximations and Methods for Radiative Transfer in Astrophysics
LiteraturGalactic Dynamics (Binney & Tremaine, Princeton University Press),
Computer Simulation using Particles (Hockney & Eastwood CRC press),
Targeted journal reviews on computational methods for astrophysical fluids (SPH, AMR, moving mesh)
Voraussetzungen / BesonderesSome knowledge of UNIX, scripting languages (see as an example), some prior experience programming, knowledge of C, C++ beneficial
651-4271-00LErdwissenschaftliche Datenanalyse und Visualisierung mit MatlabW3 KP3GS. Wiemer, G. De Souza, T. Tormann
KurzbeschreibungDie Vorlesung und dazugehörige Übung geben den Studierenden eine Einführung in die Konzepte und Werkzeuge der wissenschaftlichen Datenanalyse. Anhand von praktischen erdwissenschaftlichen Problemstellungen werden in Kleingruppen und Einzelarbeit Aufgaben von wachsender Komplexität mit der Software MATLAB gelöst. Dabei lernen die Studierenden auch, Datensätze effektvoll zu visualisieren.
LernzielDie folgenden Konzepte werden vorgestellt:
- Effektvolle Datenanalyse und Visualisierung in 2D und 3D
- Arbeiten mit Matrizen und Arrays
- Programmieren und Algorithmenentwicklung
- Animationen sinnvoll einsetzen
- Einen Datensatz statistisch erfassen
- Interaktives Datamining
- Unsicherheiten, Fehlerfortpflanzung und Bootstrapping
- Regressionsanalysen
- Testen von Hypothesen
151-3217-00LCoaching studentischer Teams (Basistraining)W1 KP1GR. P. Haas, I. Goller, M. Lehner, B. Volk
KurzbeschreibungZiel ist die Erweiterung von Wissen und Kompetenzen in Bezug auf Coaching-Fähigkeiten. Teilnehmende sollten aktive Coaches eines Studententeams sein. Themen: Überblick über Rollen und Haltung eines Coaches, Einführung in die Coaching-Methodik. Gegenseitiges Lernen und Reflektieren der eigenen Coaching-Erfahrungen und -fälle.
Lernziel- Grundkenntnisse der Rolle und Denkweise eines Coaches
- Erste Kenntnisse und Reflexion klassischer Coaching Situationen
- Inspiration und gegenseitiges Lernen an konkreten Coachings (Hospitationen)
InhaltGrundkenntnisse der Rolle und Denkweise eines Coaches
- Coaching-Einführung: Definition und Modelle
- Einführung in den Coaching-Prozess und die Phasen der Teamentwicklung
- Coaching-Rollen zwischen Prüfendem, Tutor und "Freund"
Erster Aufbau der persönlichen Coaching-Kompetenzen, z. B aktives Zuhören, Fragestellung, Feedback geben
- Kompetenzen in theoretischen Modellen
- Coaching-Kompetenzen: Übungen und Reflektion
Erste Reflektion und Erfahrungsaustausch über persönliche Coaching-Situationen
- Erfahrungsaustausch in der Vorlesungsgruppe
- Gegenseitige Hospitationen
SkriptFolien und andere Dokumente (z.B. Artikel) werden elektronisch verteilt
(Zugang nur für den Kurs eingeschriebene Studierende).
LiteraturSiehe Skript.
Voraussetzungen / BesonderesNur für Teilnehmer (Studierende. Doktoranden und PostDocs), die die aktiv ein studentisches Projektteam betreuen.
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