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Learner Reviews & Feedback for Process Mining: Data science in Action by Eindhoven University of Technology

4.7
stars
1,218 ratings

About the Course

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....

Top reviews

RK

Jul 1, 2019

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.

PP

Dec 9, 2019

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.

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26 - 50 of 310 Reviews for Process Mining: Data science in Action

By Niyi O

Apr 21, 2017

Brilliant course. Would fully recommend

By Evgeny I

Jun 11, 2017

Rather complicated but great course

By Henning B

Aug 13, 2017

Interesting material, but the course seems mostly designed to cross-sell the book and promote the (open source) software of the authors, rather then promote understanding of the underlying algorithms.

Positive: The videos go through examples in great detail.

By Radu - A C

Jul 13, 2019

I am surprised to have learned so many new topics and methods for data science in one course. It's like opening a pack of trading cards (e.g. Pokemon TCG or Yu-Gi-Oh cards) and finding that you don't have any duplicates. I think the knowledge in this course is a great addition to the skill set of any data scientist (regardless if you currently work or not with processes). Finally kudos to Prof. van der Aalst and his team. Very well planned lectures, quality content and no boring quizzes. I think it would be good for the future to add more quiz variations, as taking a quiz twice to improve one's answer one will work with exactly the same questions and numbers. I would also like to see a future Process Mining course, with more in-depth lectures on the topics of conformance checking and enhancement. A more practical side would also be welcome, for example coding some algorithms.

By Testing

Apr 22, 2021

Having such great content for free is just amazing. I would like to thank all of the team for their effort. But I would give it a 4,5 if I could because the algorithm parts of the course was quite dull although the topic is so easy to spice up a little bit. Also another constructive feedback would be to have some more details on creating the event log. A walkthroguh together with the professor would be amazing. Because creating the log seems to be the most complicated step of the whole process since other parts are made easier thanks to tools and without the log we cant have process mining. I would really be interested if you could just show us a demo on how to create a basic log from an ERP system such as SAP.

By Marcus B

Mar 27, 2019

Very good, very thorough course - especially because of the many exercises strewn across the videos. The subject matter is not trivial - I often feel the need to re-read material in the accompanying text book, and it's taking me many weeks to find the time to complete this course. The videos, in my view, are too long. This means that there should probably be twice as many videos (they should not be longer than 10 min), or some of the material ought to be left out - mostly foundational stuff. Doing that would, however, invalidate the course as a stand alone introduction - I give full stars because it is in my experience, really hard to pull all of this off. Could only be done by a true expert like van der Aalst.

By Tom T

Oct 7, 2021

Excellent course content and excellent presentation. Among the best explanations I've seen for Petri Nets, Entropy in Decision Trees, quality metrics for models, etc. Some of the topics are highly technical and require careful mathematical/logical thought and practice to learn. Overall, a good balance of theory and applications, though. Very comprehensive set of skills to understand algorithms and practical application of Process Mining. Thank you for providing all the course slides as PDF. It's great that the course offers examples from a couple different software tools, including the open-source ProM.

By Paulien L

Jun 10, 2019

I'm a novice to data science and took this course after an (offline) post graduate education Big Data Analyst. I learned about Disco during that training. With this Coursera-course I wanted to know more in detail about procesmining.

Though it was quite jejune and theoretical sometimes I found it interesting and doable enough. With the exams, practising and assignment alltogether I feel it did come to live as well. So I made it to the end and feel happy and proud to complete this course. Many thanks to the team om TU/e!

By Subendhu D

Feb 26, 2024

Generally very informative, with a great mix of theory and application. Some of the example walkthrough's could have been a little more detailed, especially when working on the later modules with with more advanced subjects. But having the material available to re-review made for an overall worthwhile experience. It would be good (more of a Coursera observation than for this specific course) if it were possible to have certification badges that could easily be added to email signatures.

By christian J c g

Aug 3, 2019

The course accomplish with its own commitment as introductory level for this useful growing tendency for process analysis using datadriven with various practical assignments, welldone explained by the professor and easy for understand from simple examples until the one´s more difficult . i liked a lot that you can use software and make simulations with real data, besides excellent complement with its book where you can go in deep about topics .

By Tatiana D C

Apr 23, 2024

I highly recommend this course to a large variety of listeners. The course provides a lot of useful information and examples related to processes in general and process mining from the very basics to the practical application. The material is perfectly prepared and very well explained. The graded assessments are of medium difficulty in average, but they still require to listen and understand the course.

By Rinus F

Dec 19, 2019

This course introduces the concept and basic principles of process mining extremely well to the user. It stimulates you to go looking for new analyses to improve business processes and gets you thinking about potential applications in your work space.

The course is simple enough for beginners, yet gives enough detail to be able to start implementation of process mining.

By Gabriela M D

Nov 30, 2022

Es el mejor curso que he realizado. Se aborda un tema muy interesante y novedoso, que me ha brindado una mejora indudable a nivel profesional como ingeniera industrial. El profesor explica con ejemplos prácticos y de forma muy clara, y el alcance del curso es amplio a pesar de ser un tema bastante extenso. ¡Felicidades al equipo y muchas gracias por ofrecer el curso!

By Deleted A

Dec 25, 2020

This course provides a gentle introduction to process mining. The content was easy to grasp. Difficult parts of the course were explained succinctly and thus could shorten the learning curve. I really recommend this course as a starter for those who want to take part in the process mining community either as a researcher, business professional, etc.

By João D V

Aug 7, 2019

This has been one of my favourite courses in Coursera. I thought it was very well organized and I greatly appreciated the attention that was given to using the tools. I also thought the quizz and assignments allowed me to identify where I needed to put more effort and review the learning material. Overall great experience!

By Dominik S

Jul 28, 2018

Very interesting topic and the course is beautifully designed. The different techniques are described in the fitting amount of detail and many examples of process mining in practice are given. Plus the two process mining tools are shown and explained so that it is possible to use them in one's one projects.

By Rodrigo C

Apr 1, 2018

This course is very useful. Its content give us a clear notion of process mining and how to apply it to discover the process model.

It helped me identifying real cases bottlenecks in my own process and my analysis are more data-based. This chance in my approach made my work more reliable and "to the point".

By simofura

Sep 20, 2016

Great great course.

I'm a beginner in this matter so to me there are cases difficult to understand. One thing that could help a lot would be more exemplas of real life for each theorical concept. As done at the beginning with coffee, latte, muffin, ect.

Thanks for the energy dedicated to create this course.

By 李正锋

Feb 20, 2021

I'm a postgraduate student from China, cost about 2 months nearly I have finished and learnt all the courses, I do learn enormously from these lectures. In my opinions, our country has not used the process mining, I can't find any about it almostly. I expect the future about the process mning technology.

By Michelle T

Apr 24, 2018

This is a very good course for those who are interested in process mining. I continue to review and improve my understanding on each concept, and one day I will be able to reap the fruit of all the process improvements through applying this in work place. Thank you very much for offering this course!

By Robin C

Aug 16, 2020

This is a brilliant course, led by a world authority on process mining who freely imparts his knowledge and presentation skills. I cannot critic it.

From a personal point of view I have learnt so much and the access to the tools makes it so tangible and valuable.

A big and sincere THANK YOU!!!

By Laurin B

Jun 30, 2023

Very nice introduction into the topic of Process Mining. The structure of the videos with always incentivized the student to think about a solution on their own. I also liked how process mining was compared/connected to other related fields such as data mining, data science and BI.

By Mikel B

Aug 13, 2021

Prof. Wil van der aalst generated a nice intuition that allowed me easily to understand the complicated notation describing the covered material. By this, I can now discover the world of process mining in my ongoing activities independently, and I look forward to it. Thanks :)

By M. C

Mar 7, 2021

One of the most interesting course I have ever attendend.

Professor Wil Van der Aalst is outstanding at explaining the different topics and elements of the course.

There are also some lectures and tutorials for Disco and ProM beninners, that were also very useful.

Thank you!

By Zahrah N M

Jun 9, 2021

Very rich material with practical examples that make you appreciate the processes that constitute a workplace. As a data scientist this course brought things closer to earth. From abstract data mining to real people and situations. Kudos to the professor and his team!