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返回到 过程挖掘：数据科学实战

学生对 埃因霍温科技大学 提供的 过程挖掘：数据科学实战 的评价和反馈

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650 个评分
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165 条评论

课程概述

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....

热门审阅

RK

Jul 02, 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 10, 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.

筛选依据：

51 - 过程挖掘：数据科学实战 的 75 个评论（共 165 个）

创建者 Bart V d W

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Jan 26, 2018

Very clear and thorough explanation of the important concepts of process mining, with enough room for exercises and hands-on practice

创建者 Maros K

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Feb 15, 2019

Great course, it covers basics of process mining, from petri net, over pm algoritms to steps how to do process mining on real data.

创建者 Caio C d V

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Nov 13, 2017

Very useful for those that are seeking knowledge about how to improve processes. I'll use it in my doctorate and also in my work!!!

创建者 Lu Z

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Sep 10, 2019

Very high-quality course. It is an intermediate level course, so expect some difficulty learning this. But it totally worth it.

创建者 Mariano A M

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Jul 24, 2017

Very well thought and laid out course. Examples throughout the lectures clearly illustrate what the Professor wants to convey.

创建者 Gad A

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Apr 16, 2019

Excellent course, it provided insights into large sets of Data and their structuring, which had not been explored before.

创建者 Kerim A

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Apr 18, 2019

very informative, amazing content, and definitely worth it. Thanks for offering such an awesome learning opportunity...

创建者 Sergei M

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Sep 15, 2017

All my expectations were achieved. I like approach of these course, theory was not boring. A lot of practice.

Thanks!

创建者 Marcela G

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Nov 16, 2016

Excellent course about Process Mining, it's explained all meant to understand process discovery with Data analysis.

创建者 Frank G

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Jan 15, 2017

这门课程十分理论知识丰富，又贴近实际应用，很棒。This course is really fantastic, it both has wonderful academical and practical knowledge.

创建者 Yuting H

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Jan 23, 2020

It's a great and well-structured course that I can gain fundamental knowledge of process mining quickly. Thanks!

创建者 Greg L

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Jan 05, 2017

very comprehensive. well structured. good pace, I would recommend having the book for reference/research.

创建者 Carlos D

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Aug 22, 2019

Outstanding!. Very well structured, The questions inside lectures really help you to get into the topic

创建者 Alix C

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Mar 29, 2018

Easy to understand and very comprehensive. Examples are challenging but help to understand everything.

创建者 Szedelényi J

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Jun 02, 2017

Guides through the fundamentals of process mining and provide hands-on skills to apply right away.

创建者 Philip S

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Dec 09, 2019

Very useful course for all data analytics fans that want to know how process mining tools work.

创建者 Arash D S

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Sep 21, 2018

This course was fantastic and I learn a lot of new ideas about data and understanding of data.

创建者 Vahid T

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Apr 04, 2018

I love this course because it really add values to organizations by improving their bottomline

创建者 Najmeh R

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Oct 22, 2016

Excellent! Well defined, practical examples and also it shows how it can be used be Prom tool.

创建者 Tom K

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Jan 08, 2017

Very good overview and provides a good foundation for further exploration in Process Mining.

创建者 Janid A

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Dec 11, 2018

The course is excellent, clear and simple and can bring improvements in many applied fields

创建者 Mustafa G

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Jun 01, 2019

Very good course overall. I wish there was more technical lessons in the last two weeks

创建者 Gilberto A

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Oct 31, 2017

Great course, good explanation and excelente selection of topics. Totally recommended!

创建者 Bart v D

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Apr 04, 2019

Very well explained, provides a good basic understanding of the topic process mining.

创建者 Secundino S

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May 28, 2017

Fantastic way to get additional insights through data mining on digitized processes