This course is on Business Intelligence (BI) 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".
- The exams have been graded. Grades have been submitted to the student administration. You can inspect your exam results on June 26 in room 157b.
Lectures: Fridays from 11:00 to 12:45 in the spring semester of 2018 in
Snellius room 412.
Werkcolleges: Fridays from 13:30 to 15:15 in room 302/304.
Lecturer: dr. Frank Takes, email@example.com, Snellius room 157b
Assistants : Gerrit-Jan de Bruin MSc, firstname.lastname@example.org, room 150 and Jasper van Nijhuis BSc, email@example.com
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%)
6 7 ECTS
|1.||Feb 9, 2018||Lecture 1: Introduction to BI & PM||Orientation on Assignment 1||v/d Aalst Chapter 1|
|2.||Feb 16, 2018||Lecture 2: Business Intelligence & Visual Analytics||Work on Assignment 1
|3.||Feb 23, 2018||Lecture 3: Descriptive Analytics||Work on Assignment 1||v/d Aalst Chapter 4|
|4.||Mar 2, 2018||Lecture 4: Predictive Analytics||Work on Assignment 1||v/d Aalst Chapter 4|
|Mar 7, 2018||Deadline for Assignment 1||Hand in via Dropbox|
|5.||Mar 9, 2018||Lecture 5: Neural Networks||scientific-python-lectures
Work on Assignment 2
|v/d Aalst Chapter 4|
|Mar 16, 2018||No lecture (cf. roosters)|
|6.||Mar 23, 2018||Lecture 6: Network Analytics||Work on Assignment 2||Kleinberg Chapter 1 and Chapter 2|
|Mar 30, 2018||No lecture (Goede vrijdag)|
|7.||Apr 6, 2018||Lecture 7: Process Modelling & Petri Nets
in room 313
|Work on Assignment 2||v/d Aalst Chapter 2 & 3|
|8.||Apr 13, 2018||Lecture 8: EventPad
(Guest lecture by Bram Cappers)
|Work on Assignment 2|
|Apr 19, 2018||Deadline for Assignment 2||Hand in via Dropbox|
|9.||Apr 20, 2018||Lecture 9: Petri Nets & BPMN||"Werkcollege" on Petri nets and answers, in room 174||v/d Aalst Chapter 3, 5 & 11|
|Apr 27, 2018||No lecture (Koningsdag)||Work on Assignment 3|
|10.||May 4, 2018||Lecture 10: Process Mining||Work on Assignment 3||v/d Aalst Chapter 6, 8 & 9|
|May 11, 2018||No lecture (day after Hemelvaartsdag)|
|11.||May 18, 2018||No lecture||Work on Assignment 3|
|12.||May 25, 2018||Lecture 11: Applications and case studies||Work on Assignment 3|
|May 30, 2018||Deadline for Assignment 3||Hand in via Dropbox|
|13.||Jun 1, 2018 at 11.15||Lecture 12: Summary & Exam preparation|
|Jun 8, 2018||Exam (14.00-17.00)||
Lecture slides, v/d Aalst (2nd edition, 2016) chapters 1,2,3,4,5,6,8,9 and 11 and understand the general ideas behind Kleinberg chapter
You can skip lecture 11, 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, 12 to 16
and any formal notation from chapter 8 onwards.
Practice: 2015 exam & answers, 2016 exam & answers and 2017 exam & answers and 2018 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 cover more business intelligence aspects. In addition, neural networks were added to the set of topics as of 2018.
|Jun 30, 2018||Retake deadline for all assignments||Note that you can also hand in (late) re-take assignments much earlier.|
|July 5, 2018||Retake exam (14.00-17.00)|
N.B. There is no class on March 16, March 30 (Goede Vrijdag), April 27 (Koningsdag), May 11 (day after Hemelvaartsdag).
On May 18, there is no lecture, but there is a lab session to work on Assignment 3.
Also see the "I&E roosters".
The business intelligence 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 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, business intelligence and process modelling finally come together in the topic of process mining: a data-driven approach to understanding business process management.
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 authors.