This course consists of around 20 lectures covering the different fields of process mining, including five process discovery techniques, three conformance checking techniques, data preparation, decision mining, predictive analytics, machine learning, big-data analytics, and process mining software. The course is at an introductory level, but also comprehensive and providing details on state-of-the-art process mining techniques. The videos are part of the Business Process Intelligence (BPI) course organized by the PADS (Process and Data Science) group at RWTH (www.pads.rwth-aachen.de) led by prof.dr.ir. Wil van der Aalst. The lectures by Wil van der Aalst are online due to COVID-19 and recorded in Spring 2021. Niklas Adams, Bianka Bakullari, Ali Norouzifar, Marco Pegoraro, Mahsa Pourbafrani, Mahnaz Qafari, Majid Rafiei, and Miriam Wagner took care of the instructions and assignments. For more information, visit http://www.vdaalst.com and http://www.pads.rwth-aachen.de. Enjoy the course! We hope it will inspire you to dive deeper into the wonderful world of process mining. Overview 1 Introduction to Process Mining 2 Decision Trees 3 Association Rules & Clustering 4 Introduction to Process Discovery 5 Petri Nets & Alpha Algorithm 6 Alpha Algorithm Continued 7 Quality of Discovered Models and Representations 8 Heuristic Mining 9 Region-Based Mining 10 Inductive Mining 11 Event Data and Exploration 12 Conformance Checking (1/2) 13 Conformance Checking (2/2) 14 Decision Mining 15 Organizational Mining & Bottleneck Analysis 16 Refined Process Mining Framework and Operational Support 17 Dealing with Big Event Data Closing Lecture (Note that the RWTH course has more lectures dedicated to the organization, exam, assignments, etc. Since these are specific, they are not included.) See https://youtube.com/playlist?list=PLG... for all lectures in this course. See https://youtube.com/playlist?list=PLG... for last years course (BPI 2020) and https://youtube.com/playlist?list=PLG... for an Introduction to Data Science (IDS 20/21). WWW: www.vdaalst.com Twitter: #processmining @wvdaalst LinkedIn: linkedin.com/in/wvdaalst
