This course is on Business Intelligence (BI) and Process Modelling (PM), and is part of the (dutch) bachelor program "Informatica & Economie" (specialization Business Information Systems) of Leiden University.News:
Lectures: Fridays from 11:15 to 13:00 in the spring semester of 2016 in
Snellius room 405.
Werkcolleges: Fridays from 13:45 to 15:30 in room 302/304.
Lecturer: dr. Frank Takes, email@example.com, Snellius room 157b
Student assistants : Thomas Prikkel BSc, firstname.lastname@example.org and Thomas Helling 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%)
Study points: 6 ECTS
|1.||Feb 3, 2017||Lecture 1: Introduction to BI & PM||Orientation on Assignment 1||v/d Aalst Chapter 1|
|2.||Feb 10, 2017||Lecture 2: Crash-course Webdevelopment||Crash-course example files
Work on Assignment 1
|3.||Feb 17, 2017||Lecture 3: Visual Analytics||Work on Assignment 1||Paper [Koo17]|
|4.||Feb 24, 2017||Lecture 4: Supervised Data Analytics||Work on Assignment 1||v/d Aalst Chapter 4|
|5.||Mar 3, 2017||Lecture 5: Unsupervised Data Analytics||Work on Assignment 1||v/d Aalst Chapter 4|
|Mar 8, 2017||Deadline for Assignment 1||Hand in via e-mail or Dropbox|
|6.||Mar 10, 2017||Lecture 6: Pandas, Matplotlib & scikit-learn||scientific-python-lectures
Orientation on Assignment 2
|7.||Mar 17, 2017||Lecture 7: Network Analytics Fundamentals||Work on Assignment 2||Kleinberg Chapter 1|
|8.||Mar 24, 2017||Lecture 8: Network Analytics Methods||Work on Assignment 2||Kleinberg Chapter 2|
|9.||Mar 31, 2017||Lecture 9: Process Modelling||Work on Assignment 2||v/d Aalst Chapter 2 & 3|
|10.||Apr 7, 2017||Lecture 10: Petri Nets||Work on Assignment 2||v/d Aalst Chapter 5 & 11|
|Apr 12, 2017||Deadline for Assignment 2||Hand in via e-mail or Dropbox|
|Apr 14, 2017||No lecture||Orientation on Assignment 3|
|11.||Apr 21, 2017||Lecture 11: BPMN
Petri nets werkcollege & answers
|Work on Assignment 3||v/d Aalst Chapter 3 & 8|
|12.||Apr 28, 2017||Lecture 12: Process Discovery||Work on Assignment 3||v/d Aalst Chapter 6 & 9|
|May 5, 2017||No lecture||Draw and practice with Petri nets.|
|13.||May 12, 2017||Lecture 13: Course summary and exam preparation||Work on Assignment 3||Everything|
|May 17, 2017||Deadline for Assignment 3||Hand in via e-mail or Dropbox|
|June 2, 2017||Exam (14:00 - 17:00)
Snellius room 407-409
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 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 precise specification of XES in 5.3, chapter 7, 10, 12 to 16
and any formal notation from chapter 8 onwards.
Practice: 2015 exam and answers, 2016 exam and answers and 2017 exam and answers.
|July 3, 2017||Retake deadline for all assignments||Note that you can also hand in late/re-taken assignments much earlier.|
|July 6, 2017||Retake exam (14:00 - 17:00)
Snellius room 174
N.B. There is no class on April 14 (Goede Vrijdag), May 5 (Bevrijdingsdag) and May 19.
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.