====== Process Mining ======
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===== News =====
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  * <wrap em>**October 2nd, 2019**</wrap>: Lessons will start!!! Enjoying. 
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===== General Info =====
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**Teachers**: 
  * Barbara Re 

**ESSE3 Link**
  * [[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
  * Wednesday: 11:00 am – 13:00 am

**To book an appointment**:
  * Please send and e-mail.


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===== Course Objectives =====

  * This course focuses on the the missing link between model-based process analysis and data-oriented analysis techniques 
  * The course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains
  * The course explains various process discovery algorithms 
  * The course introduce conformance techniques to compare processes and event data
  * The course provides to students the opportunity to experiment with tools


===== Learning Outcomes =====

  * At the end of the course, the students will gain familiarity with process mining terminology, methodology and technologies
  * Be able to apply basic process discovery techniques to learn a process model from an event log  
  * Be able to apply basic conformance checking techniques to compare event logs and process models  
  * Have a good understanding of the data needed to start a process mining project
  * Be able to conduct process mining projects




===== Course Contents =====

  * Introduction
    * From Internet of Events to Process Mining
    * Logs: Play-in, Play Out and Reply
    * 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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** Course Slides **

  * {{ :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}}
  * {{ :didattica:magistrale:pm:ay_1920:gettingdata.pdf |Getting Data}}
  * {{ :didattica:magistrale:pm:ay_1920:processdiscoveryanintroduction.pdf |Process Discovery an Introduction}}
  * {{ :didattica:magistrale:pm:ay_1920:processdiscoveryanintroduction.pdf |Alpha Algorithm: A Process Discovery Algorithm}}
  * {{ :didattica:magistrale:pm:ay_1920:processdiscoveryintroduction.pdf |Alpha Algorithm: Limitation}}
  *  {{ :didattica:magistrale:pm:ay_1920:advancedprocessdiscoverytechniques.pdf |Quality, Heuristic and Genetic mining}}
  * {{ :didattica:magistrale:pm:ay_1920:simonelli.pdf |Mining Experience}} ({{ :didattica:magistrale:pm:ay_1920:final_version_published.pdf |comparison}}) ({{ :didattica:magistrale:pm:ay_1920:bustech_2017_1_30_90020.pdf |methodology}})
  * {{ :didattica:magistrale:pm:ay_1920:04_conformance.pdf |Conformance Checking}}
  * {{ :didattica:magistrale:pm:ay_1920:05_additional.pdf |Mining Additional Perspectives}}
 




 

**Reference book:**
  * Process Mining: Data Science in Action by W.M.P. van der Aalst, Springer Verlag, 2016 (ISBN 978-3-662-49850-7).  

**Tools:**
  * Apromore   - http://apromore.unicam.it/ 
  * Disco -  https://fluxicon.com/disco/
  * ProM - http://www.promtools.org/


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===== Exams =====
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**Dates available at 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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