Eindhoven University of Technology Courses

Sports and Building Aerodynamics

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeCOURSE ABSTRACT: Have we reached the boundaries of what can be achieved in sports and building design? The answer is definitely “NO”. This course explains basic aspects of bluff body aerodynamics, wind tunnel testing and Computational Fluid Dynamics (CFD) simulations with application to sports and building aerodynamics. It is intended for anyone with a strong interest in these topics. Key fields addressed are urban physics, wind engineering and sports aerodynamics.COURSE CONTENTS:The course consists of 6 weeks. The first 3 weeks are on fundamentals, the second 3 weeks on applications.- Week 1: Basic aspects of fluid flow- Week 2: Wind-tunnel testing- Week 3: Computational Fluid Dynamics- Week 4: Building aerodynamics- Week 5: 100 m sprint aerodynamics- Week 6: Cycling aerodynamicsCOURSE UPGRADES:In January-February 2017, the course will be upgraded/extended with:- New modules on cycling aerodynamics- Week 7: Climate adaptation of buildings and cities- Week 8: Air pollutionIf you want to take the upgraded/extended course, please wait with enrollment until mid February.LECTURER:The lecturer is Bert Blocken, professor at Eindhoven University of Technology in the Netherlands and KU Leuven in Belgium. He is a Civil Engineer holding a PhD in Building Physics. His main areas of expertise are urban physics, wind engineering and sports aerodynamics. He has published 126 papers in international peer-reviewed journals. He has received the 2013 Junior Award from the International Association of Wind Engineering and six best paper awards from the Elsevier ISI journal Building & Environment (2009, 2011, 2012) and at international conferences. According to the 2016 Academic Ranking of World Universities (Shanghai Ranking) & Elsevier, he is among the 150 most cited researchers world-wide both in the field of Civil Engineering and in the field of Energy Science & Engineering. Since Dec 2016, he is editor of the ISI journal Building & Environment and starting 2017, he is also associate editor of the ISI Journal of Wind Engineering & Industrial Aerodynamics. He is member of the editorial board of the ISI journals Building Simulation and Sports Engineering. He has acted as a reviewer for more than 70 different ISI journals. He is currently supervising a team of 4 senior researchers, 32 PhD students and 5 MSc students.

Microwave engineering and antennas

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis unique Master-level course provides you with in-depth know-how of microwave engineering and antennas. The course combines both passive and active microwave circuits as well as antenna systems. Future applications, like millimeter-wave 5G/beyond-5G wireless communications or automotive radar, require experts that can co-design highly integrated antenna systems that include both antennas and microwave electronics. We will provide you with the required theoretical foundation as well as hands-on experience using state-of-the-art design tools.The web lectures are supported by many on-line quizzes in which you can practice the background theory. Next to this, we will provide you hands-on experience in a design-challenge in which you will learn how to design microwave circuits and antennas. Throughout the course you will work on the design challenge in which you will design a complete active phased array system, including antennas, beamformers and amplifiers. The course is supported by a book written by the team of lecturers, which will be made available to the students. After finalizing the course a certificate can be obtained (5 ECTS), which can be used when you start a full MSc program at Eindhoven University of Technology. The lecturers all have an academic and industrial background and are embedded in the Center for Wireless Technology Eindhoven (CWT/e) of Eindhoven University of Technology, The Netherlands.

Process Mining in Healthcare

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Learn how to get the most from healthcare data using process miningWithin healthcare there are thousands of complex and variable processes that generate data including treatment of patients, lab results and internal logistic processes. Analysing this data is vital for improving these processes and ending bottlenecks.On this course you will explore how process mining can help turn this data into valuable insights by looking at different areas of process mining and seeing how it has been applied. You will even get the chance to apply process mining on real life healthcare data.This course is for healthcare experts who want to find out more about using data to solve problems and execute ideas. It will also be of interest to process mining enthusiasts who want to know more about the application of process mining to healthcare. You don’t need any prior experience, just a keen interest in the topic.We strongly advise you to carry out the process mining activities using the data provided in this course. For this we will be using our free and open source tool ProM lite. Please download the most recent ProM lite version from www.promtools.org.

Introduction to Process Mining with ProM

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Learn to get a critical, process-centric perspective on dataProcess mining combines business process management with data science. Using process mining, you can analyse and visualise business processes based on event data recorded in event logs.For example, you could analyse how people use public transportation; verify whether a loan application is processed correctly by a bank; or predict when hardware parts are likely to fail.This online course will give you an introduction to this new and exciting field.This course is designed for anyone with an interest in business process management (BPM), data science and/or process analytics. No specific prior knowledge is required, only a healthy interest is required.We do however require you to have a computer with internet access ready on which you can install and use ProM. Please refer to www.promtools.org for more information regarding ProM.

Improving Your Statistical Questions

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions. In practical hands on assignments you will learn techniques and tools that can be immediately implemented in your own research, such as thinking about the smallest effect size you are interested in, justifying your sample size, evaluate findings in the literature while keeping publication bias into account, performing a meta-analysis, and making your analyses computationally reproducible.If you have the time, it is recommended that you complete my course 'Improving Your Statistical Inferences' before enrolling in this course, although this course is completely self-contained.

Process Mining: Data science in Action

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeProcess mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains.Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action".The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains.This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments.The course covers the three main types of process mining.1. The first type of process mining is discovery. A discovery technique takes an event log and produces a process model without using any a-priori information. An example is the Alpha-algorithm that takes an event log and produces a process model (a Petri net) explaining the behavior recorded in the log.2. The second type of process mining is conformance. Here, an existing process model is compared with an event log of the same process. Conformance checking can be used to check if reality, as recorded in the log, conforms to the model and vice versa.3. The third type of process mining is enhancement. Here, the idea is to extend or improve an existing process model using information about the actual process recorded in some event log. Whereas conformance checking measures the alignment between model and reality, this third type of process mining aims at changing or extending the a-priori model. An example is the extension of a process model with performance information, e.g., showing bottlenecks. Process mining techniques can be used in an offline, but also online setting. The latter is known as operational support. An example is the detection of non-conformance at the moment the deviation actually takes place. Another example is time prediction for running cases, i.e., given a partially executed case the remaining processing time is estimated based on historic information of similar cases.Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development.The course uses many examples using real-life event logs to illustrate the concepts and algorithms. After taking this course, one is able to run process mining projects and have a good understanding of the Business Process Intelligence field.After taking this course you should:- have a good understanding of Business Process Intelligence techniques (in particular process mining),- understand the role of Big Data in today’s society,- be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification,- be able to apply basic process discovery techniques to learn a process model from an event log (both manually and using tools),- be able to apply basic conformance checking techniques to compare event logs and process models (both manually and using tools),- be able to extend a process model with information extracted from the event log (e.g., show bottlenecks),- have a good understanding of the data needed to start a process mining project,- be able to characterize the questions that can be answered based on such event data,- explain how process mining can also be used for operational support (prediction and recommendation), and- be able to conduct process mining projects in a structured manner.

Ethics, Technology and Engineering

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThere is an increasing attention to ethics in engineering practice. Engineers are supposed not only to carry out their work competently and skilfully, but also to be aware of the broader ethical and social implications of engineering and to be able to reflect on these.According to the Engineering Criteria 2000 of the Accreditation Board for Engineering and Technology (ABET) in the US, engineers must have “an understanding of professional and ethical responsibility” and should "understand the impact of engineering solutions in a global and societal context.” This course provides an introduction to ethics in engineering and technology. It helps engineers and students in engineering to acquire the competences mentioned in the ABET criteria or comparable criteria formulated in other countries. More specifically, this course helps engineers to acquire the following moral competencies:- Moral sensibility: the ability to recognize social and ethical issues in engineering;- Moral analysis skills: the ability to analyse moral problems in terms of facts, values, stakeholders and their interests;- Moral creativity: the ability to think out different options for action in the light of (conflicting) moral values and the relevant facts;- Moral judgement skills: the ability to give a moral judgement on the basis of different ethical theories or frameworks including professional ethics and common sense morality;- Moral decision-making skills: the ability to reflect on different ethical theories and frameworks and to make a decision based on that reflection.With respect to these competencies, our focus is on the concrete moral problems that engineers encounter in their professional practice. With the help of concrete cases is shown how the decision to develop a technology, as well as the process of design and production, is inherently moral. The attention of the learners is drawn towards the specific moral choices that engineers face. In relation to these concrete choices learners will encounter different reasons for and against certain actions, and they will discover that these reasons can be discussed. In this way, learners become aware of the moral dimensions of technology and acquire the argumentative capacities that are needed in moral debates with stakeholders (e.g. governments, users, and commercial business departments).

RF and millimeter-Wave Circuit Design

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Class Central TipsLearn How to Sign up to Coursera courses for free1600+ Coursera Courses That Are Still Completely FreeThis unique Master-level course offered by the Center for Wireless Technology Eindhoven (CWT/e) of the Eindhoven University of Technology, The Netherlands, provides students with in-depth knowledge and hands-on experience on RF and mmWave circuit design.The course covers the topics on how to derive the RF wireless systems specifications, and how to design the main building blocks of a transceiver, i.e., low noise amplifier, power amplifier, RF mixers, oscillators, and PLL frequency synthesizers. It is divided into two parts: (1) theoretical lectures will cover the basis of RF and mmWave Circuit Design; and (2) design labs will include simulation and implementation of these circuits.The design labs are completely optional for obtaining the certificate, but they are recommended because they allow students to put into practice all the acquired theoretical knowledge, and of course, implementing the circuits is where all the fun is! The students will be able to do 70% of the design labs using simulation tools, which already offers a great learning experience. The other 30% will require students to either get access to an electronics lab or to purchase a few off-the-shelf components. But ultimately, this would allow students to design and build their own transceiver at home!The course contains theoretical video classes with examples, quizzes, and an entire set of simulation files, step-by-step procedures, recorded data of real-life circuits, and solution videos so that students can learn from and build even better circuits.