Search result: Catalogue data in Autumn Semester 2019
Computer Science Bachelor | ||||||
Minor Courses | ||||||
5. Semester | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
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102-0227-00L | Systems Analysis and Mathematical Modeling in Urban Water Management Number of participants limited to 50. | W | 6 credits | 4G | E. Morgenroth, M. Maurer | |
Abstract | Systematic introduction of material balances, transport processes, kinetics, stoichiometry and conservation. Ideal reactors, residence time distribution, heterogeneous systems, dynamic response of reactors. Parameter identification, local sensitivity, error propagation, Monte Carlo simulation. Introduction to real time control (PID controllers). Extensive coding of examples in Berkeley Madonna. | |||||
Objective | The goal of this course is to provide the students with an understanding and the tools to develop their own mathematical models, to plan experiments, to evaluate error propagation and to test simple process control strategies in the field of process engineering in urban water management. | |||||
Content | The course will provide a broad introduction into the fundamentals of modeling water treatment systems. The topics are: - Introduction into modeling and simulation - The material balance equations, transport processes, transformation processes (kinetics, stoichiometry, conservation) - Ideal reactors - Hydraulic residence time distribution and modeling of real reactors - Dynamic behavior of reactor systems - Systems analytical tools: Sensitivity, parameter identification, error propagation, Monte Carlo simulation - Introduction to process control (PID controller, fuzzy control) | |||||
Lecture notes | Copies of overheads will be made available. | |||||
Literature | There will be a required textbook that students need to purchase: Willi Gujer (2008): Systems Analysis for Water Technology. Springer-Verlag, Berlin Heidelberg | |||||
Prerequisites / Notice | General understanding of urban water management. This course will be offered together with the course Process Engineering Ia. It is advantageous to follow both courses simultaneously. | |||||
151-0573-00L | System Modeling | W | 4 credits | 2V + 2U | L. Guzzella | |
Abstract | Introduction to system modeling for control. Generic modeling approaches based on first principles, Lagrangian formalism, energy approaches and experimental data. Model parametrization and parameter estimation. Basic analysis of linear and nonlinear systems. | |||||
Objective | Learn how to mathematically describe a physical system or a process in the form of a model usable for analysis and control purposes. | |||||
Content | This class introduces generic system-modeling approaches for control-oriented models based on first principles and experimental data. The class will span numerous examples related to mechatronic, thermodynamic, chemistry, fluid dynamic, energy, and process engineering systems. Model scaling, linearization, order reduction, and balancing. Parameter estimation with least-squares methods. Various case studies: loud-speaker, turbines, water-propelled rocket, geostationary satellites, etc. The exercises address practical examples. | |||||
Lecture notes | The handouts in English will be sold in the first lecture. | |||||
Literature | A list of references is included in the handouts. | |||||
151-0575-01L | Signals and Systems | W | 4 credits | 2V + 2U | A. Carron | |
Abstract | Signals arise in most engineering applications. They contain information about the behavior of physical systems. Systems respond to signals and produce other signals. In this course, we explore how signals can be represented and manipulated, and their effects on systems. We further explore how we can discover basic system properties by exciting a system with various types of signals. | |||||
Objective | Master the basics of signals and systems. Apply this knowledge to problems in the homework assignments and programming exercise. | |||||
Content | Discrete-time signals and systems. Fourier- and z-Transforms. Frequency domain characterization of signals and systems. System identification. Time series analysis. Filter design. | |||||
Lecture notes | Lecture notes available on course website. | |||||
Prerequisites / Notice | Control Systems I is helpful but not required. | |||||
151-0591-00L | Control Systems I | W | 4 credits | 2V + 2U | L. Guzzella | |
Abstract | Analysis and controller synthesis for linear time invariant systems with one input and one output signal (SISO); transition matrix; stability; controllability; observability; Laplace transform; transfer functions; transient and steady state responses. PID control; dynamic compensators; Nyquist theorem. | |||||
Objective | Identify the role and importance of control systems in everyday life. Obtain models of single-input single-output (SISO) linear time invariant (LTI) dynamical systems. Linearization of nonlinear models. Interpret stability, observability and controllability of linear systems. Describe and associate building blocks of linear systems in time and frequency domain with equations and graphical representations (Bode plot, Nyquist plot, root locus). Design feedback controllers to meet stability and performance requirements for SISO LTI systems. Explain differences between expected and actual control results. Notions of robustness and other nuisances such as discrete time implementation. | |||||
Content | Modeling and linearization of dynamic systems with single input and output signals. State-space description. Analysis (stability, reachability, observability, etc.) of open-loop systems. Laplace transformation, systems analysis in the frequency domain. Transfer functions and analysis of the influence of its poles and zeros on the system's dynamic behavior. Frequency response. Analysis of closed-loop systems using the Nyquist criterion. Formulation of performance constraints. Specification of closed-loop system behavior. Synthesis of elementary closed-loop control systems (PID, lead/lag compensation, loop shaping). Discrete time state space representation and stability analysis. | |||||
Lecture notes | Analysis and Synthesis of Single-Input Single-Output Control Systems, Lino Guzzella, vdf Hochschulverlag. The textbook is offered for sale at the beginning of the semester. In addition, the slides of the lecture will be put online. | |||||
Literature | Analysis and Synthesis of Single-Input Single-Output Control Systems, Lino Guzzella, vdf Hochschulverlag. The textbook is offered for sale at the beginning of the semester. | |||||
Prerequisites / Notice | Basic knowledge of (complex) analysis and linear algebra. | |||||
151-0601-00L | Theory of Robotics and Mechatronics | W | 4 credits | 3G | P. Korba, S. Stoeter | |
Abstract | This course provides an introduction and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control. | |||||
Objective | Robotics is often viewed from three perspectives: perception (sensing), manipulation (affecting changes in the world), and cognition (intelligence). Robotic systems integrate aspects of all three of these areas. This course provides an introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control. | |||||
Content | An introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control. | |||||
Lecture notes | available. | |||||
151-0709-00L | Stochastic Methods for Engineers and Natural Scientists Number of participants limited to 45. | W | 4 credits | 3G | D. W. Meyer-Massetti | |
Abstract | The course provides an introduction into stochastic methods that are applicable for example for the description and modeling of turbulent and subsurface flows. Moreover, mathematical techniques are presented that are used to quantify uncertainty in various engineering applications. | |||||
Objective | By the end of the course you should be able to mathematically describe random quantities and their effect on physical systems. Moreover, you should be able to develop basic stochastic models of such systems. | |||||
Content | - Probability theory, single and multiple random variables, mappings of random variables - Estimation of statistical moments and probability densities based on data - Stochastic differential equations, Ito calculus, PDF evolution equations - Polynomial chaos and other expansion methods All topics are illustrated with engineering applications. | |||||
Lecture notes | Detailed lecture notes will be provided. | |||||
Literature | Some textbooks related to the material covered in the course: Stochastic Methods: A Handbook for the Natural and Social Sciences, Crispin Gardiner, Springer, 2010 The Fokker-Planck Equation: Methods of Solutions and Applications, Hannes Risken, Springer, 1996 Turbulent Flows, S.B. Pope, Cambridge University Press, 2000 Spectral Methods for Uncertainty Quantification, O.P. Le Maitre and O.M. Knio, Springer, 2010 | |||||
151-3217-00L | Coaching Students (Basic Training) | W | 1 credit | 1G | B. Volk, R. P. Haas, M. Lehner | |
Abstract | Aim is enhancement of knowledge and competency regarding coaching skills. Participants should be active coaches of a student team. Topics: Overview of the roles and mind set of a coach as, introduction into coaching methodology, mutual learning and reflecting of participants coaching expertise and situations. | |||||
Objective | - Basic knowledge about role and mindset of a coach - Basic Knowledge and reflection about classical coaching situations - Inspiration and mutual learning from real coaching sessions (mutual peer observation) | |||||
Content | Basic knowledge about role and mindset of a coach - Introduction into coaching: definition & models - Introduction into the coaching process and team building phases - Role of coaches between examinator, tutor and ""friend"" First steps building up personal coaching competencies, i.e. active listening, asking questions, giving feedback - Competencies in theoretical models - Coaching competencies: exercises and reflection Some Reflection and exchange of experiences about personal coaching situations - Exchange of experiences in the lecture group - Mutual peer observations | |||||
Lecture notes | Slides, script and other documents will be distributed electronically (access only for participants registered to this course) | |||||
Literature | Please refer to lecture script. | |||||
Prerequisites / Notice | Participants (Students, PhD Students, Postdocs) should be actively coaching students. | |||||
227-0076-00L | Electrical Engineering II | W | 4 credits | 2V + 2U | J. Biela | |
Abstract | Sinusoidal signals and systems in the time and frequency domain, principle of operation and design of basic analog and digital circuits as well as analog-digital conversion. Basic power electronic circuits, design of magnetic components, electromechanical energy conversion, principle of operation and characteristics of transformators and selected rotating electrical machines. | |||||
Objective | see above | |||||
Content | Beschreibung von sinusförmigen Signalen und Systemen im Zeit- und Frequenzbereich, Funktion grundlegender analoger und digitaler Schaltungen sowie von Analog-Digital-Wandlern. Grundlagen leistungselektronischer Konverter, Berechnung magnetischer Kreise, elektromechanische Energiewandlung, Funktionsprinzip von Transformatoren und ausgewählter rotierender elektrischer Maschinen. | |||||
227-0116-00L | VLSI I: From Architectures to VLSI Circuits and FPGAs | W | 6 credits | 5G | F. K. Gürkaynak, L. Benini | |
Abstract | This first course in a series that extends over three consecutive terms is concerned with tailoring algorithms and with devising high performance hardware architectures for their implementation as ASIC or with FPGAs. The focus is on front end design using HDLs and automatic synthesis for producing industrial-quality circuits. | |||||
Objective | Understand Very-Large-Scale Integrated Circuits (VLSI chips), Application-Specific Integrated Circuits (ASIC), and Field-Programmable Gate-Arrays (FPGA). Know their organization and be able to identify suitable application areas. Become fluent in front-end design from architectural conception to gate-level netlists. How to model digital circuits with SystemVerilog. How to ensure they behave as expected with the aid of simulation, testbenches, and assertions. How to take advantage of automatic synthesis tools to produce industrial-quality VLSI and FPGA circuits. Gain practical experience with the hardware description language SystemVerilog and with industrial Electronic Design Automation (EDA) tools. | |||||
Content | This course is concerned with system-level issues of VLSI design and FPGA implementations. Topics include: - Overview on design methodologies and fabrication depths. - Levels of abstraction for circuit modeling. - Organization and configuration of commercial field-programmable components. - FPGA design flows. - Dedicated and general purpose architectures compared. - How to obtain an architecture for a given processing algorithm. - Meeting throughput, area, and power goals by way of architectural transformations. - Hardware Description Languages (HDL) and the underlying concepts. - SystemVerilog - Register Transfer Level (RTL) synthesis and its limitations. - Building blocks of digital VLSI circuits. - Functional verification techniques and their limitations. - Modular and largely reusable testbenches. - Assertion-based verification. - Synchronous versus asynchronous circuits. - The case for synchronous circuits. - Periodic events and the Anceau diagram. - Case studies, ASICs compared to microprocessors, DSPs, and FPGAs. During the exercises, students learn how to model FPGAs with SystemVerilog. They write testbenches for simulation purposes and synthesize gate-level netlists for FPGAs. Commercial EDA software by leading vendors is being used throughout. | |||||
Lecture notes | Textbook and all further documents in English. | |||||
Literature | H. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303. | |||||
Prerequisites / Notice | Prerequisites: Basics of digital circuits. Examination: In written form following the course semester (spring term). Problems are given in English, answers will be accepted in either English oder German. Further details: Link | |||||
227-0731-00L | Power Market I - Portfolio and Risk Management | W | 6 credits | 4G | D. Reichelt, G. A. Koeppel | |
Abstract | Portfolio and risk management in the electrical power business, Pan-European power market and trading, futures and forward contracts, hedging, options and derivatives, performance indicators for the risk management, modelling of physical assets, cross-border trading, ancillary services, balancing power market, Swiss market model | |||||
Objective | Knowlege on the worldwide liberalisation of electricity markets, pan-european power trading and the role of power exchanges. Understand financial products (derivatives) based on power. Management of a portfolio containing physical production, contracts and derivatives. Evaluate trading and hedging strategies. Apply methods and tools of risk management. | |||||
Content | 1. Pan-European power market and trading 1.1. Power trading 1.2. Development of the European power markets 1.3. Energy economics 1.4. Spot and OTC trading 1.5. European energy exchange EEX 2. Market model 2.1. Market place and organisation 2.2. Balance groups / balancing energy 2.3. Ancillary services 2.4. Market for ancillary services 2.5. Cross-border trading 2.6. Capacity auctions 3. Portfolio and Risk management 3.1. Portfolio management 1 (introduction) 3.2. Forward and futures contracts 3.3. Risk management 1 (m2m, VaR, hpfc, volatility, cVaR) 3.4. Risk management 2 (PaR) 3.5. Contract valuation (HPFC) 3.6. Portfolio management 2 2.8. Risk Management 3 (enterprise wide) 4. Energy & Finance I 4.1. Options 1 – basics 4.2. Options 2 – hedging with options 4.3. Introduction to derivatives (swaps, cap, floor, collar) 4.4. Financial modelling of physical assets 4.5. Trading and hydro power 4.6. Incentive regulation | |||||
Lecture notes | Handouts of the lecture | |||||
Prerequisites / Notice | 1 excursion per semester, 2 case studies, guest speakers for specific topics. Course Moodle: Link | |||||
227-0945-00L | Cell and Molecular Biology for Engineers I This course is part I of a two-semester course. | W | 3 credits | 2G | C. Frei | |
Abstract | The 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. | |||||
Objective | After 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. | |||||
Content | Lectures will include the following topics (part I and II): 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, 4 journal clubs will be held, where recent publications will be discussed (2 journal clubs in part I and 2 journal clubs in part II). 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 40% for the final grade. | |||||
Lecture notes | Scripts of all lectures will be available. | |||||
Literature | "Molecular Biology of the Cell" (6th edition) by Alberts, Johnson, Lewis, Raff, Roberts, and Walter. | |||||
227-2037-00L | Physical Modelling and Simulation | W | 6 credits | 4G | J. Smajic | |
Abstract | This module consists of (a) an introduction to fundamental equations of electromagnetics, mechanics and heat transfer, (b) a detailed overview of numerical methods for field simulations, and (c) practical examples solved in form of small projects. | |||||
Objective | Basic knowledge of the fundamental equations and effects of electromagnetics, mechanics, and heat transfer. Knowledge of the main concepts of numerical methods for physical modelling and simulation. Ability (a) to develop own simple field simulation programs, (b) to select an appropriate field solver for a given problem, (c) to perform field simulations, (d) to evaluate the obtained results, and (e) to interactively improve the models until sufficiently accurate results are obtained. | |||||
Content | The module begins with an introduction to the fundamental equations and effects of electromagnetics, mechanics, and heat transfer. After the introduction follows a detailed overview of the available numerical methods for solving electromagnetic, thermal and mechanical boundary value problems. This part of the course contains a general introduction into numerical methods, differential and integral forms, linear equation systems, Finite Difference Method (FDM), Boundary Element Method (BEM), Method of Moments (MoM), Multiple Multipole Program (MMP) and Finite Element Method (FEM). The theoretical part of the course finishes with a presentation of multiphysics simulations through several practical examples of HF-engineering such as coupled electromagnetic-mechanical and electromagnetic-thermal analysis of MEMS. In the second part of the course the students will work in small groups on practical simulation problems. For solving practical problems the students can develop and use own simulation programs or chose an appropriate commercial field solver for their specific problem. This practical simulation work of the students is supervised by the lecturers. | |||||
252-4900-00L | Didactic Basics for Student Teaching Assistants @ ETH | W | 1 credit | G. Serafini | ||
Abstract | Didaktische Ausbildung für Hilfsassistierende | |||||
Objective | Die Lehrassistierenden… - geben sich gegenseitig Feedback auf ihre Lehre und reflektieren ihre Unterrichtspraxis. - verstehen die Grundlagen von Lehre und Lernen im Kontext ihres Unterrichtsfachs. - fühlen sich sicher, aktivierende Lehrmethoden in ihrer Unterrichtspraxis anzuwenden. | |||||
Content | - Theoretische Grundlagen - Peerhospitation - Kollegialer Unterrichtsbesuch mit Feedback - Transferveranstaltung - Was nehme ich aus der Ausbildung, der Peerhospitation und der konkreten Unterrichtserfahrung mit? | |||||
351-0778-00L | Discovering 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. | W | 3 credits | 3G | B. Clarysse, S. Brusoni, E. Fleisch, G. Grote, V. Hoffmann, T. Netland, G. von Krogh, F. von Wangenheim | |
Abstract | Discovering 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. | |||||
Objective | Discovering 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. | |||||
Content | Discovering 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. | |||||
Prerequisites / Notice | Discovering 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. | |||||
351-0778-01L | Discovering Management (Exercises) Complementary exercises for the module Discovering Managment. Prerequisite: Participation and successful completion of the module Discovering Management (351-0778-00L) is mandatory. | W | 1 credit | 1U | B. Clarysse, L. De Cuyper | |
Abstract | This course is offered complementary to the basis course 351-0778-00L, "Discovering Management". The course offers additional exercises and case studies. | |||||
Objective | This course is offered to complement the course 351-0778-00L. The course offers additional exercises and case studies. | |||||
Content | The course offers additional exercises and case studies concering: Strategic Management; Technology and Innovation Management; Operations and Supply Chain Management; Finance and Accounting; Marketing and Sales. Please refer to the course website for further information on the content, credit conditions and schedule of the module: Link | |||||
363-0541-00L | Systems Dynamics and Complexity | W | 3 credits | 3G | F. Schweitzer | |
Abstract | Finding solutions: what is complexity, problem solving cycle. Implementing solutions: project management, critical path method, quality control feedback loop. Controlling solutions: Vensim software, feedback cycles, control parameters, instabilities, chaos, oscillations and cycles, supply and demand, production functions, investment and consumption | |||||
Objective | A successful participant of the course is able to: - understand why most real problems are not simple, but require solution methods that go beyond algorithmic and mathematical approaches - apply the problem solving cycle as a systematic approach to identify problems and their solutions - calculate project schedules according to the critical path method - setup and run systems dynamics models by means of the Vensim software - identify feedback cycles and reasons for unintended systems behavior - analyse the stability of nonlinear dynamical systems and apply this to macroeconomic dynamics | |||||
Content | Why are problems not simple? Why do some systems behave in an unintended way? How can we model and control their dynamics? The course provides answers to these questions by using a broad range of methods encompassing systems oriented management, classical systems dynamics, nonlinear dynamics and macroeconomic modeling. The course is structured along three main tasks: 1. Finding solutions 2. Implementing solutions 3. Controlling solutions PART 1 introduces complexity as a system immanent property that cannot be simplified. It introduces the problem solving cycle, used in systems oriented management, as an approach to structure problems and to find solutions. PART 2 discusses selected problems of project management when implementing solutions. Methods for identifying the critical path of subtasks in a project and for calculating the allocation of resources are provided. The role of quality control as an additional feedback loop and the consequences of small changes are discussed. PART 3, by far the largest part of the course, provides more insight into the dynamics of existing systems. Examples come from biology (population dynamics), management (inventory modeling, technology adoption, production systems) and economics (supply and demand, investment and consumption). For systems dynamics models, the software program VENSIM is used to evaluate the dynamics. For economic models analytical approaches, also used in nonlinear dynamics and control theory, are applied. These together provide a systematic understanding of the role of feedback loops and instabilities in the dynamics of systems. Emphasis is on oscillating phenomena, such as business cycles and other life cycles. Weekly self-study tasks are used to apply the concepts introduced in the lectures and to come to grips with the software program VENSIM. Another objective of the self-study tasks is to practice efficient communication of such concepts. These are provided as home work and two of these will be graded (see "Prerequisites"). | |||||
Lecture notes | The lecture slides are provided as handouts - including notes and literature sources - to registered students only. All material is to be found on the Moodle platform. More details during the first lecture | |||||
Prerequisites / Notice | The end-of-semester examination will account for 70% of the grade and may be conducted on computers. The self-study tasks contribute to the compulsory continuous performance assessment (obligatorisches Leistungselement) and account for 30% to the final grade. The Leistungselement contains several modules: one obligatory self-study tasks (self-assessment, pass/fail), one group activity (one out of 3 group exercises, 15% of grade), and one individual submission (one out of 6 individual exercises, 15% of grade). Students will also be required to submit peer feedback about self-study solutions of other students (4 feedback submissions in total). The 30% Leistungselement is conditional on the pass/fail self-assessment exercise and the four feedback submissions. | |||||
363-1082-00L | Enabling Entrepreneurship: From Science to Startup Students should provide a brief overview (unto 1 page) of their business ideas that they would like to commercialise through the course. If they do not have an idea, they are required to provide a motivation letter stating why they would like to do this elective. If you are unsure about the readiness of your idea or technology to be converted into a startup, please drop me a line to schedule a call or meeting to discuss. The total number of students will be limited to 40. It is preferable that the students already form teams of at least two persons, where both the team-members would like to do the course. The names of the team-members should be provided together with the business idea or the motivation letter submitted by the students. The students should submit the necessary information and apply to Link. | W | 3 credits | 2V | A. Sethi | |
Abstract | Participants form teams and identify an idea, which is then taken through the steps necessary to form a startup. The primary focus of the course is geared to technology startups that want to reach scale. | |||||
Objective | Participants want to become entrepreneurs. Participants can be from business or science & technology The course will enable the students to identify an idea and take all necessary steps to convert it into a company, through the duration of the two semesters. The participants will have constant exposure to investors and entrepreneurs (with a focus on ETH spin-offs) through the course, to gain an understanding of their vision and different perspectives. | |||||
Content | Participants start from idea identification, forming team, technology and market size validation, assessing time-to-market, customer focus, IP strategy & financials, to become capable of starting the company and finally making the pitch to investors. The seminar comprises lectures, talks from invited investors regarding the importance of the various elements being covered in content, workshops and teamwork. There is a particular emphasis on market validation on each step of the journey, to ensure the relevance of the idea, relevance to customers, time to market and customer value. | |||||
Literature | Book Sethi, A. "From Science to Startup" ISBN 978-3-319-30422-9 | |||||
Prerequisites / Notice | This course is only relevant for those students who aspire to become entrepreneurs. Students applying for this course are requested to submit a 1 page business idea or, in case they don't have a business idea, a brief motivation letter stating why they would like to do this course. The course will be in two modules (autumn and spring), which will run in two consecutive semesters. Priority for the second semester will be given to those students who have attended the first semester. If you are unsure about the readiness of your idea or technology to be converted into a startup, please drop me a line to schedule a call or meeting to discuss. | |||||
363-1109-00L | Introduction to Microeconomics GESS (Science in Perspective): This course is only for students enrolled in a Bachelor’s degree programme. Students enrolled in a Master’s degree programme may attend “Principles of Microeconomics” (LE 363-0503-00L) instead. Note for D-MAVT students: If you have already successfully completed “Principles of Microeconomics” (LE 363-0503-00L), then you will not be permitted to attend it again. | W | 3 credits | 2G | M. Wörter, M. Beck | |
Abstract | The course introduces basic principles, problems and approaches of microeconomics. It describes economic decisions of households and firms, and their coordination through perfectly competitive markets. | |||||
Objective | Students acquire a deeper understanding of basic microeconomic models. They acquire the ability to apply these models in the interpretation of real world economic contexts. Students acquire a reflective and contextual knowledge on how societies use scarce resources to produce goods and services and distribute them among themselves. | |||||
Content | Market, budget constraint, preferences, utility function, utility maximisation, demand, technology, profit function, cost minimisation, cost functions, perfect competition, information and communication technologies | |||||
Lecture notes | Course material in e-learning environment Link | |||||
Literature | Varian, Hal R. (2014), Intermediate Microeconomics, W.W. Norton | |||||
Prerequisites / Notice | This course "Einführung in die Mikroökonomie“ (363-1109-00L) is intended for Bachelor students and LE 363-0503-00 "Principles of Microeconomics" for Master students. | |||||
376-1177-00L | Human Factors I | W | 3 credits | 2V | M. Menozzi Jäckli, R. Huang, M. Siegrist | |
Abstract | Every 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. | |||||
Objective | The 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. | |||||
Content | - 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 | |||||
Literature | - 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 | |||||
401-0353-00L | Analysis 3 | W | 4 credits | 2V + 2U | M. Iacobelli | |
Abstract | In this lecture we treat problems in applied analysis. The focus lies on the solution of quasilinear first order PDEs with the method of characteristics, and on the study of three fundamental types of partial differential equations of second order: the Laplace equation, the heat equation, and the wave equation. | |||||
Objective | The aim of this class is to provide students with a general overview of first and second order PDEs, and teach them how to solve some of these equations using characteristics and/or separation of variables. | |||||
Content | 1.) General introduction to PDEs and their classification (linear, quasilinear, semilinear, nonlinear / elliptic, parabolic, hyperbolic) 2.) Quasilinear first order PDEs - Solution with the method of characteristics - COnservation laws 3.) Hyperbolic PDEs - wave equation - d'Alembert formula in (1+1)-dimensions - method of separation of variables 4.) Parabolic PDEs - heat equation - maximum principle - method of separation of variables 5.) Elliptic PDEs - Laplace equation - maximum principle - method of separation of variables - variational method | |||||
Literature | Y. Pinchover, J. Rubinstein, "An Introduction to Partial Differential Equations", Cambridge University Press (12. Mai 2005) | |||||
Prerequisites / Notice | Prerequisites: Analysis I and II, Fourier series (Complex Analysis) |
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