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--- didattica:magistrale:pm:ay_1920:main [2019/10/01 23:18]
barbara [Learning Outcomes]
+++ didattica:magistrale:pm:ay_1920:main [2020/09/17 16:55] (current)
@@ Line 3: / Line 3: @@
 ===== News =====
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-  * <wrap em>**January 14th, 2019**</wrap>: On Thursday January 17th there will be no lesson
+  * <wrap em>**October 2nd, 2019**</wrap>: Lessons will start!!! Enjoying.
-  * <wrap em>**October 25th, 2018**</wrap>: Dear student due to an unforeseen engagement I cannot deliver today's lesson.
-  * October 2nd, 2018: Next lesson will be delivered on October 4th
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 **ESSE3 Link**
-  * [[https://didattica.unicam.it/Guide/PaginaADContest.do;jsessionid=C355AE2BA49C150FC9B2CCADFF2DCBCA.esse3-unicam-prod-02?ad_cont_id=10025*8952*2018*2016*9999&ANNO_ACCADEMICO=2018&ANNO_COORTE=2018&ANNO_REVISIONE=2018|Process Mining - AY 2018/2019]]
+  * [[https://didattica.unicam.it/Guide/PaginaADContest.do?ad_cont_id=10025*8952*2019*2016*9999&ANNO_ACCADEMICO=2019&ANNO_COORTE=2019&ANNO_REVISIONE=2019|Process Mining - AY 2019/2020]]
 **Lessons Scheduling:**
   * 42 h - lecture and exercise sessions
-  * Monday: 2:00 PM – 4:00 PM
+  * Monday: 2:00 pm – 4:00 pm
-  * Thursday: 2:00 PM – 4:00 PM
+  * Wednesday: 11:00 am – 13:00 am
+**To book an appointment**:
+  * Please send and e-mail.
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 ===== Course Contents =====
-  * Introduction to Process Mining and Data Mining. Data. Logs. Play-in, Play Out and Reply. Fundamentals of Process Modelling.
+  * Introduction
-  * From Event Logs to Process Models. Getting Data. Process Discovery. Discovery Techniques an Introduction.  Tools support an introduction: Apromore, Disco, and ProM.
+    * From Internet of Events to Process Mining
-  * Discovery Algorithms. Alfa,  Heuristic, Genetic Miner.
+    * Logs: Play-in, Play Out and Reply
-  * Conformance Checking. Business Alignment and Auditing. Token Replay. Process Drift. Business Process Model and Instances. Business Process Life-Cycle. Classification of Business Process.
+    * Positioning Process Mining
+  * Preliminaries
+    * Process Modelling and Analysis
+    * Data Mining
+  * From Event Logs to Process Models
+    * Getting Data
+    * Process Discovery
+    * Advance Process Discovery Techniques
+    * Tools support
+  * Beyond Process Discovery
+    * Conformance Checking
+    * Mining Additional Perspective
+  * Putting Process Mining to Work
+    * Business Activity Monitoring, KPI and Improvement
+    * Blockchain Technologies
+    * Sensors, Internet-of-Things (IoT) and wearable devices
 ===== Study material =====
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-** Classes Scheduling **
-  * {{ :didattica:magistrale:pm:ay_1920:scheduling_process_mining_-_foglio1.pdf |tentative}}
 ** Course Slides **
-  * {{ :didattica:magistrale:pm:ay_1920:slide_1_-_course_presentation.pdf | Course Introduction}}
-  * {{ :didattica:magistrale:pm:ay_1920:01_context.pdf |Process Mining and its Context}}
+  * {{ :didattica:magistrale:pm:ay_1920:slide_1_-_course_presentation_2019-20_.pdf |Course Introduction}}
+  * {{ :didattica:magistrale:pm:ay_1920:01_context.pdf |Process Mining and its Context}} (new!!!)
   * {{ :didattica:magistrale:pm:ay_1920:02_modeling.pdf |Formal Modeling of Processes}}
   * {{ :didattica:magistrale:pm:ay_1920:03_datamining.pdf |Data Mining - a short introduction}}
@@ Line 76: / Line 98: @@
-** Streaming **
-  * October 8th, 2019
-  * [[https://unicam.webex.com/unicam/ldr.php?RCID=fe2bfba5c2586a1fb53df3f6df3967d3|January 7th, 2019]]
-  * [[https://unicam.webex.com/unicam/ldr.php?RCID=6b05f179855dc44ac9c7db863fcfc483|January 14th, 2019]]
-  * [[https://unicam.webex.com/unicam/ldr.php?RCID=04a7a61b1160c7f5e88c3c73e4573688|January 21st, 2019]]
 **Reference book:**
-  * Process Mining: Data Science in Action by W.M.P. van der Aalst, Springer Verlag, 2016 (ISBN 978-3-662-49850-7). From chapter 1 to 9.
+  * Process Mining: Data Science in Action by W.M.P. van der Aalst, Springer Verlag, 2016 (ISBN 978-3-662-49850-7).
 **Tools:**
@@ Line 97: / Line 114: @@
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-**Project Based on 2018 Business Process Intelligence Challenge (BPIC) - [[https://www.win.tue.nl/bpi/doku.php?id=2018:challenge]] **
+**Dates available at https://didattica.unicam.it/Home.do**
-**Project Based Examination** on the topics of the syllabus including project presentation
-  - Process Mining Challenge: (i) we will provide real data set, (ii) we will provide questions to be answered
-  - We expect that you can focus on a specific aspect of interest and analyze this aspect in great detail using any technique, method, algorithm, and tool
-  - We will judge based on: (i) the originality of the results, (ii) the validity of the claims, and (iii) the depth of the analysis of specific issues identified
-**Dates** (https://didattica.unicam.it/Home.do)
+**Exams Rules**:
+  * ** Written test (2 h).** On the exam date a written test takes place, it has a mixed structure: solution of exercises, and open/close answer questionnaire.
+  * **Realisation of a project** with a software tool presented during the course writing of a report. There is an **oral discussion. {{ :didattica:magistrale:pm:ay_1920:process_mining_-_project_guidelines.pdf |Guidelines}}**.
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