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學生對 埃因霍温科技大学 提供的 过程挖掘:数据科学实战 的評價和反饋

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Process 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....




The course is designed and presented by professor aptly for beginners. I think before reading the Process Mining book it is good to take this course and then read the book later. The quizzes are good.



Good content, very thorough, and I learned a LOT! Took more time than suggested, as I learn by taking notes and reproducing diagrams. But the course structure allowed for frequent pauses to do this.


51 - 过程挖掘:数据科学实战 的 75 個評論(共 279 個)

創建者 Xavier B


Clear, easy to understand, focused on cases, uses parallel pictures to describe concepts (like maps/process mining), never boring but a lot of information to acquire and a different mindset to develop. Great course, thanks a lot, happy to have succeed

創建者 Matthias A


Excellent course! It gives a very good introduction to process mining, a rather new data science discipline that is not yet used in many companies, and therefore has a great potential in the future. So attending this course is highly recommendable.

創建者 Rony S


In depth course for process mining. Anyone trying to jump into a career on Business processes, or wants to apply data science to business processes, should take this course. It is more involved than other Data Science course, so give it your all.

創建者 Agbéti B A


Excellent cours, pour peu que l'on ait une fois suivi un cours de data mining, on voit très vite une chance de se spécialiser. De même que pour un business process analyste, il en ressort une nette opportunité d'étendre son champ d'expertise.

創建者 John R


Awesome Course, great lectures, the data that is available to use for ProM and Disco really made the difference. I would recommend this course for anyone interested in process analytics or Lean/ Six Sigma business process optimization.

創建者 Matthew M


This course is intense and informative. The material is well-presented and the assignments have clearly benefitted a great deal of care from the instructors. Process Mining a fine complement to the more typical data science coursework.

創建者 Kirill D


Great course! Well balanced theoretical information and practical exercises. Algorythms were explained in easy for understanding way. Thank you very much, Wil van der Aalst, Joos Buijs, and the rest of the Process Mining team!

創建者 Balázs H


It was very useful and clear to understand course, I would love to have a course with deeper insight on the topic, and one which is just considering the practical use-cases separately, both based on this knowledge.

創建者 Simin M


This course was extremely well-organized and well-presented by the best teacher ever. The quizzes and assignments were designed perfectly so that the most important parts discussed in lectures could stick in mind.

創建者 Geoff A


Excellent introduction to the topic of process mining. The delivery of the course was very easy to use. The course notes were excellent. Thanks very much to Professor van der Aalst for sharing his knowledge.

創建者 Phil P


Good content, very thorough, and I learned a LOT! Took more time than suggested, as I learn by taking notes and reproducing diagrams. But the course structure allowed for frequent pauses to do this.

創建者 Gabriel A F G


Un curso interesante. Para mi este tema era completamente nuevo y aun así pude entender las ideas básicas ya que el profesor es concreto en sus explicaciones y todo lo ejemplifica varias veces.

創建者 Willem R


Very interesting as an introduction to Process Mining. I believe the course laid the right foundation to understand the functioning of process mining software such as Disco and ProM.

創建者 Alberto D


Very well structured curse. Perfect introduction. Perfect level of detail when you want to know and do not have some but not solid knowledge in the Algorithms and academic base.

創建者 Carlos C A


It is a great introduction in process mining and there are a lot of examples in the videos which makes it very practical!. Thanks for the course Professor Wil van der Aalst.

創建者 Daiana E H


Es un curso desafiante. Felicito a todo el equipo detrás del mismo, muy interesante todo lo expuesto y las lecciones son excelente. Sé que me será muy útil en mi carrera.

創建者 Gert J L


Great introductory course. The book on which the course is based is a great asset. Very nice to be able to see process mining in action with the tools you can download.

創建者 Andreas B


An excellent course on a very interesting and promising topic. Many thanks to Wil van der Aalst and his team for the great introduction to the world of process mining.

創建者 Pierre-Yves N


Excellent balance between theory, simple examples and real-life situations. Language is clear and the level of complexity appropriately defined. Two thumbs up!

創建者 Stefan W


Very in-depth and well-presented material. The quizzes are quite involved, but form a rigorous basis for testing comprehension and ability to apply material.

創建者 Nikolai B


This well-focused course provides both theoretical knowledge and practical skills, which could be implemented in real life of most managers (in anersons.

創建者 Toni R


Very good overview of process mining. Excellent lectures and material. The assignments were very well balanced and grasped the essentials of lectures.

創建者 Chan J J


Very well planned and delivery by Prof was exceptional! I will definitely be interested to learn of more such courses from the university of Eindhoven

創建者 Klim M


The course material was very well explained during the lectures. The course gave a very good overview of the PM field and its practical applications.

創建者 Onur D


I'm very glad to participate in the course. I decided to use Process Mining in my PhD thesis. Thank you Prof. van der Aalst. I hope, we meet one day.