Search result: Catalogue data in Spring Semester 2020
|Integrated Building Systems Master|
|101-0579-00L||Infrastructure Management 2: Evaluation Tools||W||4 credits||2G||B. T. Adey, C. Kielhauser|
|Abstract||This course provides tools to predict the service being provided by infrastructure in situations where the infrastructure is expected to |
1) to evolve slowly with relatively little uncertainty over time, e.g. due to the corrosion of a metal bridge, and
2) to change suddenly with relatively large uncertainty, e.g. due to being washed away from an extreme flood.
|Objective||The course learning objective is to equip students with tools to be used to the service being provided from infrastructure.|
The course increases a student's ability to analyse complex problems and propose solutions and to use state-of-the-art methods of analysis to assess complex problems
Availability and maintainability
|Lecture notes||All necessary materials (e.g. transparencies and hand-outs) will be distributed before class.|
|Literature||Appropriate reading material will be assigned when necessary.|
|Prerequisites / Notice||Although not an official prerequisite, it is perferred that students have taken the IM1:Process course first. Understanding of the infrastructure management process enables a better understanding of where and how the tools introduced in this course can be used in the management of infrastructure.|
|102-0516-01L||Environmental Impact Assessment||W||3 credits||2G||S.‑E. Rabe|
|Abstract||Focus of the course are the method, the process and content of the Environmental Impact Assessment (EIA) as well as the legal bases and methods for compiling an environmental impact study (EIS).|
Using examples, a comprehensive view of the EIA is made possible by means of excursions.
In the frame of a project the process of am EIA will be workt out by the students.
|Objective||- Understanding the context of spatial planning and environmental protection|
- Ability to use central planning instruments and procedures for assessing the environmental impacts and risks of projects
- Ability to apply quantitative methods to assess the environmental impacts and risks of projects
- Knowledge about the process and content of an EIA
- a capacity for critical review of environmental impact assessments
|Content||- Nominal and functional environmental protection in Switzerland|
- Instruments of environmental protection
- Need for coordination between environmental protection and spatial planning
- Environmental Protection and environmental impact assessment
- Legal basis of the EIA
- Procedure of EIA
- Content of the EIA
- Content and structure of the EIS
- Application of the impact analysis
- Monitoring and Controlling
- View regarding the strategic environmental assessment (SEA)
- Excursions projects obligated under the EEA
|Lecture notes||No script. The documents for the lecture can be found for download on the homepage of the Chair of Planning of Landscape and Urban Systems.|
|Literature||- Bundesamt für Umwelt 2009: UVP-Handbuch. Richtlinie des Bundes|
für die Umweltverträglichkeitsprüfung. Umwelt-Vollzug Nr. 0923,
Bern. 156 S.
- Leitfäden zur UVP (werden in der Vorlesung bekannt gegben)
|Prerequisites / Notice||Additional information on mode of examination:|
No calculators allowed
|103-0357-00L||Environmental Planning||W||3 credits||2G||M. Sudau, S.‑E. Rabe|
|Abstract||The lecture covers tools, methods and procedures of|
Landscape and Environmental Planning developed. By means of field trips their implementation will be illustrated.
|Objective||Knowledge of the various instruments and possibilities for the practical implementation of environmental planning.|
Knowledge of the complex interactions of the instruments.
|Content||- forest planning|
- Intervention and compensation
- ecological network
- agricultural policy
- landscape development concepts (LEK)
- swiss concept of landscape
- riverine zone
- natural hazards
- field trips
|Lecture notes||- lecture notes concerning the instruments|
- Copies of selected literature
|Prerequisites / Notice||Additional information on mode of examination:|
No calculators allowed
|151-0102-00L||Fluid Dynamics I||W||6 credits||4V + 2U||T. Rösgen|
|Abstract||An introduction to the physical and mathematical foundations of fluid dynamics is given.|
Topics include dimensional analysis, integral and differential conservation laws, inviscid and viscous flows, Navier-Stokes equations, boundary layers, turbulent pipe flow. Elementary solutions and examples are presented.
|Objective||An introduction to the physical and mathematical principles of fluid dynamics. Fundamental terminology/principles and their application to simple problems.|
|Content||Phenomena, applications, foundations|
dimensional analysis and similitude; kinematic description; conservation laws (mass, momentum, energy), integral and differential formulation; inviscid flows: Euler equations, stream filament theory, Bernoulli equation; viscous flows: Navier-Stokes equations; boundary layers; turbulence
|Lecture notes||Lecture notes (extended formulary) for the course are made available electronically.|
|Literature||Recommended book: Fluid Mechanics, Kundu & Cohen & Dowling, 6th ed., Academic Press / Elsevier (2015).|
|Prerequisites / Notice||Voraussetzungen: Physik, Analysis|
|151-0212-00L||Advanced CFD Methods||W||4 credits||2V + 1U||P. Jenny|
|Abstract||Fundamental and advanced numerical methods used in commercial and open-source CFD codes will be explained. The main focus is on numerical methods for conservation laws with discontinuities, which is relevant for trans- and hypersonic gas dynamics problems, but also CFD of incompressible flows, Direct Simulation Monte Carlo and the Lattice Boltzmann method are explained.|
|Objective||Knowing what's behind a state-of-the-art CFD code is not only important for developers, but also for users in order to choose the right methods and to achieve meaningful and accurate numerical results. Acquiring this knowledge is the main goal of this course.|
Established numerical methods to solve the incompressible and compressible Navier-Stokes equations are explained, whereas the focus lies on finite volume methods for compressible flow simulations. In that context, first the main theory and then numerical schemes related to hyperbolic conservation laws are explained, whereas not only examples from fluid mechanics, but also simpler, yet illustrative ones are considered (e.g. Burgers and traffic flow equations). In addition, two less commonly used yet powerful approaches, i.e., the Direct Simulation Monte Carlo (DSMC) and Lattice Boltzmann methods, are introduced.
For most exercises a C++ code will have to be modified and applied.
|Content||- Finite-difference vs. finite-element vs. finite-volume methods|
- Basic approach to simulate incompressible flows
- Brief introduction to turbulence modeling
- Theory and numerical methods for compressible flow simulations
- Direct Simulation Monte Carlo (DSMC)
- Lattice Boltzmann method
|Lecture notes||Part of the course is based on the referenced books. In addition, the participants receive a manuscript and the slides.|
|Literature||"Computational Fluid Dynamics" by H. K. Versteeg and W. Malalasekera.|
"Finite Volume Methods for Hyperbolic Problems" by R. J. Leveque.
|Prerequisites / Notice||Basic knowledge in|
- fluid dynamics
- numerical mathematics
- programming (programming language is not important, but C++ is of advantage)
|151-0318-00L||Ecodesign - Environmental-Oriented Product Development||W||4 credits||3G||R. Züst|
|Abstract||Ecodesign has a great potential to improve the environmental performance of a product. |
Main topics of the lecture: Motivation for Ecodesign; Methodical basics (defining environmental aspects; improvement strageies and measures); Ecodesign implementation (systematic guidance on integrating environmental considerations into product development) in a small project.
|Objective||Experience shows that a significant part of the environmental impact of a business venture is caused by its own products in the pre and post-production areas. The goal of eco design is to reduce the total effect of a product on the environment in all phases of product life. The systematic derivation of promising improvement measures at the start of the product development process is a key skill that will be taught in the lectures.|
The participants will discover the economic and ecological potential of ECODESIGN and acquire competence in determining goal-oriented and promising improvements and will be able to apply the knowledge acquired on practical examples.
|Content||Die Vorlesung ist in drei Blöcke unterteilt. Hier sollen die jeweiligen Fragen beantwortet werden:|
A) Motivation und Einstieg ins Thema: Welche Material- und Energieflüsse werden durch Produkte über alle Lebensphasen, d.h. von der Rohstoffgewinnung, Herstellung, Distribution, Nutzung und Entsorgungen verursacht? Welchen Einfluss hat die Produktentwicklung auf diese Auswirkungen?
B) Grundlagen zum ECODESIGN PILOT: Wie können systematisch – über alle Produktlebensphasen hinweg betrachtet – bereits zu Beginn der Produktentwicklung bedeutende Umweltauswirkungen erkannt werden? Wie können zielgerichtet diejenigen Ecodesign-Maßnahmen ermittelt werden, die das größte ökonomische und ökologische Verbesserungspotential beinhalten?
C) Anwendung des ECODESIGN PILOT: Welche Produktlebensphasen bewirken den größten Ressourcenverbrauch? Welche Verbesserungsmöglichkeiten bewirken einen möglichst großen ökonomischen und ökologischen Nutzen?
Im Rahmen der Vorlesung werden verschiedene Praktische Beispiel bearbeitet.
|Lecture notes||Für den Einstieg ins Thema ECODESIGN wurde verschiedene Lehrunterlagen entwickelt, die im Kurs zur Verfügung stehen und teilwesie auch ein "distance learning" ermöglichen:|
Lehrbuch: Wimmer W., Züst R.: ECODESIGN PILOT, Produkt-Innovations-, Lern- und Optimierungs-Tool für umweltgerechte Produktgestaltung mit deutsch/englischer CD-ROM; Zürich, Verlag Industrielle Organisation, 2001. ISBN 3-85743-707-3
CD: im Lehrbuch inbegriffen (oder Teil "Anwenden" on-line via: www.ecodesign.at)
Internet: www.ecodesign.at vermittelt verschiedene weitere Zugänge zum Thema. Zudem werden CD's abgegeben, auf denen weitere Lehrmodule vorhanden sind.
|Literature||Hinweise auf Literaturen werden on-line zur Verfügung gestellt.|
|Prerequisites / Notice||Testatbedingungen: Abgabe von zwei Übungen|
|227-0216-00L||Control Systems II||W||6 credits||4G||R. Smith|
|Abstract||Introduction to basic and advanced concepts of modern feedback control.|
|Objective||Introduction to basic and advanced concepts of modern feedback control.|
|Content||This course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues.|
|Lecture notes||The slides of the lecture are available to download.|
|Literature||Skogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005.|
|Prerequisites / Notice||Prerequisites:|
Control Systems or equivalent
|151-0660-00L||Model Predictive Control||W||4 credits||2V + 1U||M. Zeilinger|
|Abstract||Model predictive control is a flexible paradigm that defines the control law as an optimization problem, enabling the specification of time-domain objectives, high performance control of complex multivariable systems and the ability to explicitly enforce constraints on system behavior. This course provides an introduction to the theory and practice of MPC and covers advanced topics.|
|Objective||Design and implement Model Predictive Controllers (MPC) for various system classes to provide high performance controllers with desired properties (stability, tracking, robustness,..) for constrained systems.|
|Content||- Review of required optimal control theory|
- Basics on optimization
- Receding-horizon control (MPC) for constrained linear systems
- Theoretical properties of MPC: Constraint satisfaction and stability
- Computation: Explicit and online MPC
- Practical issues: Tracking and offset-free control of constrained systems, soft constraints
- Robust MPC: Robust constraint satisfaction
- Nonlinear MPC: Theory and computation
- Hybrid MPC: Modeling hybrid systems and logic, mixed-integer optimization
- Simulation-based project providing practical experience with MPC
|Lecture notes||Script / lecture notes will be provided.|
|Prerequisites / Notice||One semester course on automatic control, Matlab, linear algebra.|
Courses on signals and systems and system modeling are recommended. Important concepts to start the course: State-space modeling, basic concepts of stability, linear quadratic regulation / unconstrained optimal control.
Expected student activities: Participation in lectures, exercises and course project; homework (~2hrs/week).
|227-0478-00L||Acoustics II||W||6 credits||4G||K. Heutschi|
|Abstract||Advanced knowledge of the functioning and application of electro-acoustic transducers.|
|Objective||Advanced knowledge of the functioning and application of electro-acoustic transducers.|
|Content||Electrical, mechanical and acoustical analogies. Transducers, microphones and loudspeakers, acoustics of musical instruments, sound recording, sound reproduction, digital audio.|
|363-0514-00L||Energy Economics and Policy|
It is recommended for students to have taken a course in introductory microeconomics. If not, they should be familiar with microeconomics as in, for example,"Microeconomics" by Mankiw & Taylor and the appendices 4 and 7 of the book "Microeconomics" by Pindyck & Rubinfeld.
|W||3 credits||2G||M. Filippini|
|Abstract||An introduction to energy economics and policy that covers the following topics: energy demand, economics of energy efficiency, investments and cost analysis, energy markets (fossil fuels,electricity and renewable energy sources), market failures and behavioral anomalies, market-based and non-market based energy policy instruments and regulation of energy industries.|
|Objective||The students will develop the understanding of economic principles and tools necessary to analyze energy issues and to formulate energy policy instruments. Emphasis will be put on empirical analysis of energy demand and supply, market failures, behavioral anomalies, energy policy instruments, investments in power plants and in energy efficiency technologies and the reform of the electric power sector.|
|Content||The course provides an introduction to energy economics principles and policy applications. The first part of the course will introduce the microeconomic foundation of energy demand and supply as well as market failures and behavioral anomalies. In a second part, we introduce the concept of investment analysis (such as the NPV), in the context of energy efficient investments. In the last part, we use the previously introduced concepts to analyze energy policies: from a government perspective, we discuss the mechanisms and implications of market oriented and non-market oriented policy instruments as well as the regulation of energy industries.|
Throughout the entire class, we combine the course material with insights from current research in energy economics. This combination will enable students to understand standard scientific literature in the field of energy economics. Moreover, the class aims to show students how to put real life situations in the energy sector in the context of insights from energy economics.
During the first part of the course a set of environmental and resource economics tools will be given to students through lectures. The applied nature of the course is achieved by discussing several papers in a seminar. To this respect, students are required to work in groups in order to prepare a presentation of a paper.
The evaluation policy is designed to verify the knowledge acquired by students during the course. For this purpose, a short group presentation will be graded. At the end of the course there will be a written exam covering the topics of the course. The final grade is obtained by averaging the presentation (20%) and the final exam (80%).
|Prerequisites / Notice||It is recommended for students to have taken a course in introductory microeconomics. If not, they should be familiar with microeconomics as in, for example, "Microeconomics" by Mankiw & Taylor and the appendices 4 and 7 of the book "Microeconomics" by Pindyck & Rubinfeld.|
|363-1000-00L||Financial Economics||W||3 credits||2V||A. Bommier|
|Abstract||This is a theoretical course on the economics of financial decision making, at the crossroads between Microeconomics and Finance. It discusses portfolio choice theory, risk sharing, market equilibrium and asset pricing.|
|Objective||The objective is to make students familiar with the economics of financial decision making and develop their intuition regarding the determination of asset prices, the notions of optimal risk sharing. However this is not a practical formation for traders. Moreover, the lecture doesn't cover topics such as market irrationality or systemic risk.|
After completing this course:
1. Students will be familiar with the economics of financial decision making and develop their intuition regarding the determination of asset prices;
2. Students will understand the intuition of market equilibrium. They will be able to solve the market equilibrium in a simple model and derive the prices of assets.
3. Students will be familiar with the representation of attitudes towards risk. They will be able to explain how risk, wealth and agents’ preferences affect the demand for assets.
4. Students will understand the notion of risk diversification.
5. Students will understand the notion of optimal risk sharing.
|Content||The following topics will be discussed:|
1. Introduction to financial assets: The first lecture provides an overview of most common financial assets. We will also discuss the formation of asset prices and the role of markets in the valuation of these assets.
2. Option valuation: this lecture focuses on options, which are a certain type of financial asset. You will learn about arbitrage, which is a key notion to understand the valuation of options. This lecture will give you the intuition of the mechanisms underlying the pricing of assets in more general settings.
3. Introduction to the economic analysis of asset markets: this chapter will familiarize you with the notion of market equilibrium and the role it plays concerning asset pricing. Relying on economic theory, we will consider the properties of the market equilibrium: In which cases does the equilibrium exist? Is it optimal? How does it depend on individual’s wealth and preferences? The concepts defined in this chapter are essential to understand the following parts of the course.
4. A simplified approach to asset markets: based on the notions introduced in the previous lectures, you will learn about the key concepts necessary to understand financial markets, such as market completeness and the no-arbitrage theorem.
5. Choice under uncertainty: this class covers fundamental concepts concerning agents’ decisions when facing risk. These models are crucial to understand how the demand for financial assets originates.
6. Demand for risk: Building up on the previous chapters, we will study portfolio choice in a simplified setting. We will discuss how asset demand varies with risk, agent’s preferences and wealth.
7. Asset prices in a simplified context: We will focus on the portfolio choices of an investor, in a particular setting called mean-variance analysis. The mean-variance analysis will be a first step to introduce the notion of risk diversification, which is essential in finance.
8. Risk sharing and insurance: in this lecture, you will understand that risk can be shared among different agents and how, under certain conditions, this sharing can be optimal. You will learn about the distinction between individual idiosyncratic risk and macroeconomic risk.
9. Risk sharing and asset prices in a market equilibrium: this course builds up on previous lessons and presents the consumption-based Capital Asset Pricing Model (CAPM). The focus will be on how consumption, assets and prices are determined in equilibrium.
|Literature||Main reading material: |
- "Investments", by Z. Bodie, A. Kane and A. Marcus, for the
introductory part of the course (see chapters 20 and 21 in
- "Finance and the Economics of Uncertainty" by G. Demange and G. Laroque, Blackwell, 2006.
- "The Economics of Risk and Time", by C. Gollier, MIT Press, 2001.
- "Intermediate Financial Theory" by J.-P. Danthine and J.B. Donaldson.
- Ingersoll, J., E., Theory of Financial Decision Making, Rowman and Littlefield Publishers.
- Leroy S and J. Werner, Principles of Financial Economics, Cambridge University Press, 2001
|Prerequisites / Notice||Basic mathematical skills needed (calculus, linear algebra, convex analysis). Students must be able to solve simple optimization problems (e.g. Lagrangian methods). Some knowledge in microeconomics would help but is not compulsory. The bases will be covered in class.|
|402-0812-00L||Computational Statistical Physics||W||8 credits||2V + 2U||O. Zilberberg|
|Abstract||Computer simulation methods in statistical physics. Classical Monte-Carlo-simulations: finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Application to Boltzmann machines. Simulation of non-equilibrium systems.|
Molecular dynamics simulations: long range interactions, Ewald summation, discrete elements, parallelization.
|Objective||The lecture will give a deeper insight into computer simulation methods in statistical physics. Thus, it is an ideal continuation of the lecture|
"Introduction to Computational Physics" of the autumn semester. In the first part students learn to apply the following methods: Classical Monte Carlo-simulations, finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Moreover, students learn about the application of statistical physics methods to Boltzmann machines and how to simulate non-equilibrium systems.
In the second part, students apply molecular dynamics simulation methods. This part includes long range interactions, Ewald summation and discrete elements.
|Content||Computer simulation methods in statistical physics. Classical Monte-Carlo-simulations: finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Application to Boltzmann machines. Simulation of non-equilibrium systems. Molecular dynamics simulations: long range interactions, Ewald summation, discrete elements, parallelization.|
|Lecture notes||Lecture notes and slides are available online and will be distributed if desired.|
|Literature||Literature recommendations and references are included in the lecture notes.|
|Prerequisites / Notice||Some basic knowledge about statistical physics, classical mechanics and computational methods is recommended.|
|529-0191-01L||Electrochemical Energy Conversion and Storage Technologies||W||4 credits||3G||L. Gubler, E. Fabbri, J. Herranz Salañer|
|Abstract||The course provides an introduction to the principles and applications of electrochemical energy conversion (e.g. fuel cells) and storage (e.g. batteries) technologies in the broader context of a renewable energy system.|
|Objective||Students will discover the importance of electrochemical energy conversion and storage in energy systems of today and the future, specifically in the framework of renewable energy scenarios. Basics and key features of electrochemical devices will be discussed, and applications in the context of the overall energy system will be highlighted with focus on future mobility technologies and grid-scale energy storage. Finally, the role of (electro)chemical processes in power-to-X and deep decarbonization concepts will be elaborated.|
|Content||Overview of energy utilization: past, present and future, globally and locally; today’s and future challenges for the energy system; climate changes; renewable energy scenarios; introduction to electrochemistry; electrochemical devices, basics and their applications: batteries, fuel cells, electrolyzers, flow batteries, supercapacitors, chemical energy carriers: hydrogen & synthetic natural gas; electromobility; grid-scale energy storage, power-to-gas, power-to-X and deep decarbonization, techno-economics and life cycle analysis.|
|Lecture notes||all lecture materials will be available for download on the course website.|
|Literature||- M. Sterner, I. Stadler (Eds.): Handbook of Energy Storage (Springer, 2019).|
- C.H. Hamann, A. Hamnett, W. Vielstich; Electrochemistry, Wiley-VCH (2007).
- T.F. Fuller, J.N. Harb: Electrochemical Engineering, Wiley (2018)
|Prerequisites / Notice||Basic physical chemistry background required, prior knowledge of electrochemistry basics desired.|
|101-0178-01L||Uncertainty Quantification in Engineering||W||3 credits||2G||S. Marelli|
|Abstract||Uncertainty quantification aims at studying the impact of aleatory and epistemic uncertainty onto computational models used in science and engineering. The course introduces the basic concepts of uncertainty quantification: probabilistic modelling of data (copula theory), uncertainty propagation techniques (Monte Carlo simulation, polynomial chaos expansions), and sensitivity analysis.|
|Objective||After this course students will be able to properly pose an uncertainty quantification problem, select the appropriate computational methods and interpret the results in meaningful statements for field scientists, engineers and decision makers. The course is suitable for any master/Ph.D. student in engineering or natural sciences, physics, mathematics, computer science with a basic knowledge in probability theory.|
|Content||The course introduces uncertainty quantification through a set of practical case studies that come from civil, mechanical, nuclear and electrical engineering, from which a general framework is introduced. The course in then divided into three blocks: probabilistic modelling (introduction to copula theory), uncertainty propagation (Monte Carlo simulation and polynomial chaos expansions) and sensitivity analysis (correlation measures, Sobol' indices). Each block contains lectures and tutorials using Matlab and the in-house software UQLab (www.uqlab.com).|
|Lecture notes||Detailed slides are provided for each lecture. A printed script gathering all the lecture slides may be bought at the beginning of the semester.|
|Prerequisites / Notice||A basic background in probability theory and statistics (bachelor level) is required. A summary of useful notions will be handed out at the beginning of the course.|
A good knowledge of Matlab is required to participate in the tutorials and for the mini-project.
|363-1038-00L||Sustainability Start-Up Seminar |
Number of participants limited to 30.
|W||3 credits||2G||A.‑K. Zobel, A. H. Sägesser|
|Abstract||Experts lead participants through a venturing process inspired by Lean and Design Thinking methodologies. The course contains problem identification, idea generation and evaluation, team formation, and the development of one entrepreneurial idea per team. A special focus is put on sustainability, in particular on climate change and renewable energy technologies specifically.|
|Objective||1. Students have experienced and know how to take the first steps towards co-creating a venture and potentially company|
2. Students reflect deeply on sustainability issues (with a focus on climate change & energy) and can formulate a problem statement
3. Students believe in their ability to bring change to the world with their own ideas
4. Students are able to apply entrepreneurial practices such as the lean startup approach
5. Students have built a first network and know how to proceed and who to approach in case they would like to take their ventures further.
|Content||This course is aimed at people with a keen interest to address sustainability issues (with a focus on climate change and renewable energy), with a curious mindset, and potentially first entrepreneurial ideas!|
The seminar consists of a mix of lectures, workshops, individual working sessions, teamwork, and student presentations/pitches. This class will be co-taught by an academic expert (studying innovation, entrepreneurship, and sustainability) and an entrepreneurship and sustainability “practitioner”. Real-world climate entrepreneurs and experts from the Swiss start-up and sustainability community will be invited to support individual sessions.
All course content is based on latest international entrepreneurship practices.
The seminar starts with an introduction to sustainability (with a special focus on climate change & energy) and entrepreneurship. Students are asked to self-select into an area of their interest in which they will develop entrepreneurial ideas throughout the course.
The first part of the course then focuses on deeply understanding sustainability problems within the area of interest. Through workshops and self-study, students will identify key design challenges, generate ideas, as well as provide systematic and constructive feedback to their peers.
In the second part of the course, students will form teams around their generated ideas. In these teams they will develop a business model and, following the lean start-up process, conduct real-life testing, as well as pivoting of these business models.
In the final part of the course, students present their insights gained from the lean start-up process, as well as pitch their entrepreneurial ideas and business models to an expert jury. The course will conclude with a session that provides students with a network and resources to further pursue their entrepreneurial journey.
|Lecture notes||All material will be made available to the participants.|
|Prerequisites / Notice||Prerequisite:|
Interest in sustainability & entrepreneurship.
1. It is not required that participants already have a business idea at the beginning of the course.
2. No legal entities (e.g. GmbH, Association, AG) need to be founded for this course.
PhD students, Msc students and MAS students from all departments. The number of participants is limited to max.30.
After subscribing you will be added to the waiting list.
The lecturers will contact you a few weeks before the start of the seminar to confirm your interest and to ensure a good mixture of study backgrounds, only then you're accepted to the course.
|363-1060-00L||Strategies for Sustainable Business |
Limited number of participants.
Registration will only be effective once confirmed by email from the organizers.
|W||2 credits||2S||J. Meuer|
|Abstract||In this course, students will learn to critically analyze strategies for sustainable business through exploring case studies on three main questions: |
1. What is sustainability in business?
2. How do I design a sustainability strategy?
3. How do I implement a sustainability strategy?
|Objective||After the course, you should be able to:|
1. Understand and explain sustainability challenges companies are facing;
2. Critique sustainability and related strategies;
3. Evaluate decisions taken by managers;
4. Suggest alternative approaches;
5. Develop action plans;
6. Reflect on strategies for sustainability in their own organizations.
You will also learn to apply a range of strategy concepts to sustainability challenges, including leadership, stakeholder management, diversification, and organizational change.
|Content||Although many companies nowadays report on their sustainability actions, only few successfully integrate sustainability into their business operations. In this seminar, we will cover three main questions that will help you to critically analyze and develop strategies for sustainable business:|
1. What is sustainability in business?
2. How do I design a sustainability strategy?
3. How do I implement a sustainability strategy?
We teach the course with the case method developed at Harvard Business School. The case studies will allow us to explore from multiple perspectives the many tensions involved in developing strategies for sustainable business. We will distribute case study materials before the sessions, as well as guidelines on how best to efficiently and effectively prepare for case study discussions. You will need to read the materials and to submit short assignments before each class.
The sessions are interactive and allow you to step into the role of decision-makers as they face key challenges in integrating sustainability. For example, we will look at the challenges of Fairphone in combining both social and economic goals. Why and how would Patagonia want to encourage customers to buy less rather than more clothing? We also step into the shoes of RWE's CEO Peter Terium as he grapples with ensuring a profitable and sustainable future for the German utility. And using a change management simulation, you will experience why certain approaches to implementing a sustainability initiative in an organization are more successful than others. Our case discussions will help you to apply strategy concepts to real-world sustainability problems and will also serve as a basis for thinking about sustainability in your own company.
|Literature||We will provide case study material and guidelines for analyzing cases to participants by email several weeks before the seminar.|
|Prerequisites / Notice||After signing up you will first be placed on the waiting list. We will contact all students on the waiting list by 1 March 2019 to confirm their participation in the seminar. If you have any questions, please don't hesitate to contact Johannes Meuer (email@example.com).|
|252-0220-00L||Introduction to Machine Learning |
Limited number of participants. Preference is given to students in programmes in which the course is being offered. All other students will be waitlisted. Please do not contact Prof. Krause for any questions in this regard. If necessary, please contact firstname.lastname@example.org
|W||8 credits||4V + 2U + 1A||A. Krause|
|Abstract||The course introduces the foundations of learning and making predictions based on data.|
|Objective||The course will introduce the foundations of learning and making predictions from data. We will study basic concepts such as trading goodness of fit and model complexitiy. We will discuss important machine learning algorithms used in practice, and provide hands-on experience in a course project.|
|Content||- Linear regression (overfitting, cross-validation/bootstrap, model selection, regularization, [stochastic] gradient descent)|
- Linear classification: Logistic regression (feature selection, sparsity, multi-class)
- Kernels and the kernel trick (Properties of kernels; applications to linear and logistic regression); k-nearest neighbor
- Neural networks (backpropagation, regularization, convolutional neural networks)
- Unsupervised learning (k-means, PCA, neural network autoencoders)
- The statistical perspective (regularization as prior; loss as likelihood; learning as MAP inference)
- Statistical decision theory (decision making based on statistical models and utility functions)
- Discriminative vs. generative modeling (benefits and challenges in modeling joint vy. conditional distributions)
- Bayes' classifiers (Naive Bayes, Gaussian Bayes; MLE)
- Bayesian approaches to unsupervised learning (Gaussian mixtures, EM)
|Literature||Textbook: Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press|
|Prerequisites / Notice||Designed to provide a basis for following courses:|
- Advanced Machine Learning
- Deep Learning
- Probabilistic Artificial Intelligence
- Seminar "Advanced Topics in Machine Learning"
|151-0306-00L||Visualization, Simulation and Interaction - Virtual Reality I||W||4 credits||4G||A. Kunz|
|Abstract||Technology of Virtual Reality. Human factors, Creation of virtual worlds, Lighting models, Display- and acoustic- systems, Tracking, Haptic/tactile interaction, Motion platforms, Virtual prototypes, Data exchange, VR Complete systems, Augmented reality, Collaboration systems; VR and Design; Implementation of the VR in the industry; Human Computer Interfaces (HCI).|
|Objective||The product development process in the future will be characterized by the Digital Product which is the center point for concurrent engineering with teams spreas worldwide. Visualization and simulation of complex products including their physical behaviour at an early stage of development will be relevant in future. The lecture will give an overview to techniques for virtual reality, to their ability to visualize and to simulate objects. It will be shown how virtual reality is already used in the product development process.|
|Content||Introduction to the world of virtual reality; development of new VR-techniques; introduction to 3D-computergraphics; modelling; physical based simulation; human factors; human interaction; equipment for virtual reality; display technologies; tracking systems; data gloves; interaction in virtual environment; navigation; collision detection; haptic and tactile interaction; rendering; VR-systems; VR-applications in industry, virtual mockup; data exchange, augmented reality.|
|Lecture notes||A complete version of the handout is also available in English.|
|Prerequisites / Notice||Voraussetzungen:|
Vorlesung geeignet für D-MAVT, D-ITET, D-MTEC und D-INF
Testat/ Kredit-Bedingungen/ Prüfung:
– Teilnahme an Vorlesung und Kolloquien
– Erfolgreiche Durchführung von Übungen in Teams
– Mündliche Einzelprüfung 30 Minuten
|063-0610-00L||The Digital in Architecture||W||2 credits||1V + 2U||F. Gramazio, M. Kohler|
|Abstract||In lecture series coupled with a series of taught exercises, the course establishes a conceptual framework of digital fabrication in architecture. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions open a debate on the digital as a driving force of a future building and architecture culture.|
|Objective||Students develop an understanding of the digital and its concepts in architecture and of current developments in the field of digital fabrication. Students learn about design strategies based on digital methods and are able to relate these to their own design approach and its wider context at the Department of Architecture. In the exercises, they learn to use Rhino 5 / Grasshopper and write their first code in Python. The aim is to equip students with the necessary intellectual and technical skills that allow them to independently deepen their engagement with the digital in the chosen design studios.|
|Content||The course consists of a lecture series coupled with a series of taught exercises. Departing from the work of Gramazio Kohler Research, the lectures establish a conceptual framework of the digital in architecture with special regard to digital fabrication. The exercises focus on simple yet powerful methods of digital, computational and algorithmic design. Two seminar sessions are dedicated to an open debate on the digital as a driving force of a future building and architecture culture.|
|Prerequisites / Notice||Pool Introduction Event:|
Informationon event on all the courses offered by the ITA (Institute of Technology in Architecture):
Monday, 17th February 2020, 11-12 h, HIB Open Space!
|376-1178-00L||Human Factors II||W||3 credits||2V||M. Menozzi Jäckli, R. Huang, M. Siegrist|
|Abstract||Strategies, abilities and needs of human at work as well as properties of products and systems are factors controlling quality and performance in everyday interactions. In Human Factors II (HF II), cognitive aspects are in focus therefore complementing the more physical oriented approach in HF I. A basic scientific approach is adopted and relevant links to practice are illustrated.|
|Objective||The goal of the lecture is to empower students in designing products and systems enabling an efficient and qualitatively high standing interaction between human and the environment, considering costs, benefits, health, well-being, and safety as well. 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.|
|Content||Cognitive factors in perception, information processing and action. Experimental techniques in assessing human performance and well-being, human factors and ergonomics in development of products and complex systems, innovation, decision taking, consumer behavior.|
|Literature||Salvendy G. (ed), Handbook of Human Factors, Wiley & Sons, 2012|
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