This course is on Data Science (DS) and Process Modelling (PM), and is part of the (dutch) bachelor program "Informatica & Economie" of Leiden University.
It is also open to students from the minor Data Science, and sometimes lectures are together with students from the "Informatica" bachelor course Data Science.
Note that until 2018, the course was called Business Intelligence and Process Modelling (BIPM), which had slightly different content.

News:
The university closed for the remainder of the semester as a result of COVID-19. We switch to weblectures and werkcolleges via Kaltura weblectures and the Kaltura live room. From now on, weekly, you can ask questions about the lectures at the beginning of the werkcollege on Wednesday at 13.30. URLs for each week will be posted in the schedule below. Weekly lectures will be available before Wednesday, 11.00 from April onwards; you are expected to have watched these by 13.30. There are some exceptions, such as the lecture by dr. Verberne on April 1 and the guest lecture on April 15. See the schedule below for relevant URLs to Kaltura (live rooms).

Exam. The exam will be online, on an individual basis. If you for any reason do not want or cannot take the exam, you have to notify the lecturer ASAP, but no later than June 1. An insufficient grade will be administrated if you do not show up at your exam date and time. The exam lasts for 30 minutes, and takes place in the DSPM Kaltura Live Room. You will get 15 questions on various topics that you are expected to answer concisely. The questions are similar to those asked in the written exams in previous years. You do not have to program, write or share your screen during the exam, but you are expected to sit behind a functioning webcam and microphone, without distractions, and should be prepared to look at examples or images shared with you by the lecturer.



Course information

Boek Lectures: Mondays, then from March onwards Wednesdays from 11:15 to 13:00 via weblectures in the Snellius building (room: see below)
Werkcolleges: From 9:15 to 11:00 in Snellius room 306/308 and 307, then 13:30 to 14:30 in a Kalture live room from March onwards
Lecturer: dr. Frank Takes, f.w.takes@liacs.leidenuniv.nl, room 157b
Assistants : Gerrit-Jan de Bruin MSc, g.j.de.bruin@liacs.leidenuniv.nl, room 126b and Martijn Vlak BSc, m.vlak@umail.leidenuniv.nl
Literature: W. van der Aalst, Process Mining: Discovery, Conformance and Enhancement of Business Processes, 2nd edition, Springer, 2016.
Examination: exam (60%) and three practical assignments (together 40%)
Spoken language: Dutch
Study points: 7 ECTS


Timetable (on-site)

  Date Room Lecture Werkcollege Literature
1. Feb 3, 2020 407-409 Lecture DSPM-1: Introduction to DS & PM No werkcollege (do validate your ULCN account
status immediately after the lecture!)
v/d Aalst Chapter 1
2. Feb 10, 2020 407-409 Lecture DS-2: Visual Analytics Work on Assignment 1 Paper [Koo17]
3. Feb 17, 2020 407-409 Lecture DS-3: Descriptive & Predictive Analytics I Work on Assignment 1 v/d Aalst Chapter 4
4. Feb 24, 2020 407-409 Lecture DS-5: Network Science Work on Assignment 1 Kleinberg Chapter 1 and 2
Mar 2, 2020 Deadline for Assignment 1: Hand in Assignment 1
5. Mar 4, 2020 407-409 Lecture DS-4: Descriptive & Predictive Analytics II Tutorial: scientific-python-lectures
Work on Assignment 2
v/d Aalst Chapter 4
6. Mar 11, 2020 407-409 Lecture DSPM-6: Neural Networks & Process Modelling Tutorial: scikit-learn
Work on Assignment 2
v/d Aalst Chapter 2 & 4
Mar 18, 2020 No lecture (Betabanenmarkt) Work on Assignment 2
Join the DSPM Kaltura live room
Mar 25, 2020 No lecture (Retakes) Work on Assignment 2
Join the DSPM Kaltura live room

Timetable (online)

  Date Room Lecture Werkcollege Literature
7. Apr 1, 2020 Lecture DS-7: Feature Extraction on Text & Data
(by dr. Suzan Verberne); (DS weblecture 1 2 3 4 5)
Work on Assignment 2
Join the DSPM Kaltura live room
v/d Aalst Chapter 4
8. Apr 8, 2020 Lecture PM-8: Petri Nets;
weblecture 0 1 2 3
"Homework": Petri Nets werkcollege (solutions)
Work on Assignment 2
Join the DSPM Kaltura live room
v/d Aalst Chapter 3
Apr 13, 2020 Deadline for Assignment 2: Hand in Assignment 2
9. Apr 15, 2020 11:15 (live): Lecture PM-9: Guest Lecture Eventpad - presentation (by dr. Bram Cappers) Tutorial: ProM
Work on Assignment 3
Join the DSPM Kaltura live room
Apr 22, 2020 No lecture Work on Assignment 3
Join the DSPM Kaltura live room
10. Apr 29, 2020 Lecture PM-10: BPMN, Event Logs & Tools;
weblecture 4 5
Petri Nets werkcollege discussion of solutions
Work on Assignment 3
Join the DSPM Kaltura live room
v/d Aalst Chapter 5 & 9
11. May 6, 2020 Lecture PM-11: Process Mining;
weblecture 6 7 8 vflipped: 6 7 8
Work on Assignment 3
Join the DSPM Kaltura live room
v/d Aalst Chapter 6 & 8
12. May 13, 2020 Lecture DSPM-12: Course summary & Exam preparation (interactive session at 13:30) Work on Assignment 3
Join the DSPM Kaltura live room
May 18, 2020 Deadline for Assignment 3: Hand in Assignment 3
Jun 8-10, 2020 Exam (between 9.00 and 15.00; spread over 3 days) - online and individually; schedule has beent sent around.
Study all lecture slides and v/d Aalst (2nd edition, 2016) chapters 1,2,3,4,5,6,8 and 9. Understand the general ideas behind Kleinberg chapter 1 & 2.
You can skip v/d Aalst sections 2.5.6 to 2.5.9, 3.2.1, 3.2.4, 3.2.6 to 3.2.8, the XES specification in 5.3, chapter 7, 10, 11, 12, 13, 14, 15 and 16, any formal notation from chapter 8 onwards, and in general any specific process model other than Petri nets and BPMN.
Practice: 2015 exam & answers, 2016 exam & answers and 2017 exam & answers, 2018 exam and answers and 2019 exam and answers
Note that over the years, the focus of the exam is shifting more towards the process modelling part of the course, given that the assignments assess more of the data science aspects. In addition, small changes sometimes occur. For example, neural networks were added in 2018.
Jun 17, 2020 Retake deadline for all assignments (e-mail to lecturer) Note that you can also hand in (late) retake assignments much earlier.
Jul 9, 2020 Retake exam (between 9.00 and 15.00) - online and individually; to be scheduled

N.B. There is no class on March 18, March 25 and April 22.


Course description (from your study guide 2019-2020 )

The data science aspects of this course deal with the ever-increasing need of organizations to analyze, visualize, mine and understand their own data. Topics include visualization, descriptive analytics and predictive analytics, but also more recent techniques such as network analytics. Each of these topics is addressed specifically in business-oriented and/or economical context, which is reflected in the course assignments and provided case studies. The process modelling aspect of this course addresses the fact that organizations must constantly optimize, update, and monitor the execution of their processes to stay competitive and efficient. These processes are developed on the basis of organizational targets and strategic goals, but of course the underlying IT landscape is also of influence on process design, development, implementation, and execution. During this course, data science and process modelling finally come together in the topic of process mining: a data-driven approach to understanding business process management.

The course was also given in 2015, 2016, 2017, 2018 and 2019.


The second part of this course heavily builds upon the book "Process Mining: Discovery, Conformance and Enhancement of Business Processes" by W. van der Aalst (2nd edition, Springer, 2016). As such, much of the materials in the lecture slides and exercises of this course originate from the book and accompanying courses by the book's author(s). Logically, all credits for these materials go the respective author(s).

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