Process Mining: Data science in Action

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7/10 stars
based on  4 reviews
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Cost FREE
Start Date TBA
Process Mining: Data science in Action

Course Details

Cost

FREE

Upcoming Schedule

  • TBA

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4715 reviews

Course Description

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.
Reviews 7/10 stars
4 Reviews for Process Mining: Data science in Action

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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

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9/10 starsCompleted
4 years, 7 months ago
I expected to learn the concepts and applications of process mining. All of this was delivered. Like: \- course material content AND presentation was excellent - the videos were extremely good - one of the best I have seen so far on coursera \- Tool Support - The tools were easy to install and easy to use - no programming required! \- Hands-on Exercises were included - so one could actually create models from logs, analyze the models and became familiar with the functionality of 2 Process Mining tools. Focus was on process discovery, performance analysis, conformance checking What I missed: \- hands-on excercises for extraction of event-logs (notice: this might be a boring task but is extremely important) - usually the majority of time in data mining projects is spent on getting, understanding, filtering, cleansing data \- hands-on exercises for more advanced topics (prediction, recommendation) / operative support settings... I expected to learn the concepts and applications of process mining. All of this was delivered. Like: \- course material content AND presentation was excellent - the videos were extremely good - one of the best I have seen so far on coursera \- Tool Support - The tools were easy to install and easy to use - no programming required! \- Hands-on Exercises were included - so one could actually create models from logs, analyze the models and became familiar with the functionality of 2 Process Mining tools. Focus was on process discovery, performance analysis, conformance checking What I missed: \- hands-on excercises for extraction of event-logs (notice: this might be a boring task but is extremely important) - usually the majority of time in data mining projects is spent on getting, understanding, filtering, cleansing data \- hands-on exercises for more advanced topics (prediction, recommendation) / operative support settings \- combination of RapidMiner / ProM While having said what I missed - it is clear that these things could or should be added in another subsequent course.
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Karthikeyan Sankaran profile image
Karthikeyan Sankaran profile image
8/10 starsCompleted
  • 4 reviews
  • 4 completed
3 years, 7 months ago
Process Mining gave me insights into an area of Data Science, which I think is largely neglected - 'Process Optimization'. In general, there is too much focus on data without an understanding of the underlying process that generates the data. This course provides the foundation to treat 'Process' at the same level of 'Data' when it comes to Data Science. I thoroughly enjoyed the lectures and assignments. Professor was great and inspirational. I felt that on the topic of Process Discovery there was a bit too much theory than necessary. All in all, a great course for a well rounded Data Scientist.
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Kristina Šekrst profile image
Kristina Šekrst profile image
8/10 starsCompleted
  • 102 reviews
  • 102 completed
3 years, 10 months ago
I was a bit late with this course, and it seemed boring, but it got my attention when I tried the tool quiz. Then I went over all the lectures again, and tried to see the applications of the theoretical models. There was a lot of Petrie net stuff going on, so if you're looking for practice mostly, this won't be fun. However, I did enjoy real-life examples, but sometimes I was a bit lost in the quizzes with all the complicated networks. Nevertheless, I always recommend this course to everyone who wants to learn about a bit neglected discipline, and I'm strongly recommending it to learn awesome new tools. The instructor was nice, and the TA Joos pretty much single-handedly answered every possible doubt in the forums, and I was hugely impressed by that. The course also features the Process Mining group on LinkedIn, and that's a nice way to stay in touch. All in all, a recommendation, but with a caveat if you're expecting more practice r... I was a bit late with this course, and it seemed boring, but it got my attention when I tried the tool quiz. Then I went over all the lectures again, and tried to see the applications of the theoretical models. There was a lot of Petrie net stuff going on, so if you're looking for practice mostly, this won't be fun. However, I did enjoy real-life examples, but sometimes I was a bit lost in the quizzes with all the complicated networks. Nevertheless, I always recommend this course to everyone who wants to learn about a bit neglected discipline, and I'm strongly recommending it to learn awesome new tools. The instructor was nice, and the TA Joos pretty much single-handedly answered every possible doubt in the forums, and I was hugely impressed by that. The course also features the Process Mining group on LinkedIn, and that's a nice way to stay in touch. All in all, a recommendation, but with a caveat if you're expecting more practice rather than theory.
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Richard Taylor profile image
Richard Taylor profile image
5/10 starsCompleted
  • 29 reviews
  • 28 completed
4 years, 8 months ago
I just finished the last week of this course and I find very difficult to write a review about this course, it has a lot of positive and negative things at the same time. I'll try to sum up the pluses and minuses I found: Positive things: \- Extremely well prepared material, lots of examples, clear explanations, top-quality video and audio. Top-notch. \- Fantastic instructor. Clear, precise and always right, the concepts are delivered in a perfect way. \- Excellent response time in the forums and support to the students. \- Very well prepared quizzes with many questions to make you learn the materials and apply the concepts to the questions. Negative things: \- The course is too long, too many topics, too many videos, it could have been split in 2, 3 or even 4 smaller courses. \- Peer Assignment: it is too long, the dataset is totally boring and uninteresting and it only counts for the distinction certificate. \- T... I just finished the last week of this course and I find very difficult to write a review about this course, it has a lot of positive and negative things at the same time. I'll try to sum up the pluses and minuses I found: Positive things: \- Extremely well prepared material, lots of examples, clear explanations, top-quality video and audio. Top-notch. \- Fantastic instructor. Clear, precise and always right, the concepts are delivered in a perfect way. \- Excellent response time in the forums and support to the students. \- Very well prepared quizzes with many questions to make you learn the materials and apply the concepts to the questions. Negative things: \- The course is too long, too many topics, too many videos, it could have been split in 2, 3 or even 4 smaller courses. \- Peer Assignment: it is too long, the dataset is totally boring and uninteresting and it only counts for the distinction certificate. \- The tools being used: Prom and Disco. Disco is a commercial tool and Prom has many flaws and bugs. \- Lectures are too long, too many videos per week and the pace is too slow. (It is ok at 1.5x video speed) I started this course with a lot of energy and liked its start very much, my interest quickly waned to the point of wanting to drop the course badly. The course fails to deliver a real world case to apply the tools being used for something interesting, something fun, something worth it. The peer assignment was a huge letdown as I was expecting a fun application of the topics learned and instead found a longer tool-quiz where you have to use Disco and Prom to process yet another boring and uninteresting dataset. My conclusion is that process-mining is a very interesting field where very cool algorithms can be applied but in the end the work is boring and tedious and the tools that we have available today are not fun to use and full of bugs. It's a good course so long and so detailed that you will learn to love or hate the topic unfortunately for me it was the second. I can give this course 1 star and 5 stars at the same time. You be the judge.
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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.