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Machine Learning for Business Analytics


Admission requirements



Many decisions in professional and private life are taken on the basis of data that come from all sorts of information systems. Business Intelligence (BI) is about the developments in the way we can use data stored in those information systems to generate new and useful information that can support executive managers in taking business decisions. BI is an umbrella term that combines the processes, technologies, and tools needed to transform data into information, information into knowledge, and knowledge into plans that drive profitable business action. BI encompasses: data warehousing, OnLine Analytical Processing (OLAP), business analytical tools, data mining, business performance and knowledge management.

The commercial interest in BI is growing due to the increasing awareness of companies that the vast amounts of data collected on customers and their behaviour contain valuable business knowledge. Different types of knowledge can be derived from data warehouses, like rules characterizing potential customer classes, knowledge classifying groups with larger risks, and so on. Quite often useful causal relations are hidden in company databases and the goal of the BI/data mining process is to induce these from the data and to represent them in meaningful ways to improve business processes, typical business cases are: cross-selling, churn in mobile communications, and risk analysis in financial services. The emphasis in this course will be on the methodological and practical aspects of BI.

Course objectives

In this course the student is given an introduction intelligent systems within the framework of BI. After this course the student has basic knowledge of

  • why computer support is needed for certain business decisions;

  • the principles of knowledge management;

  • why a data warehouse is needed;

  • the business implications of a data warehouse;

  • OLAP database technology and reporting;

  • the fundamental issues of knowledge discovery in databases, such as learning algorithms for classification, prediction and risk analysis;

  • a key data mining models: decision trees and/or neural networks;

In addition, the skill objective for the course is to give the student some hands on experience with BI software. By working with the software in the course and at home the student has to develop basic knowledge to analyze a simple data set with R.


You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.

MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).

For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.

Mode of instruction

interactive lectures.

Assessment method

Final grade (F) = 0.7∙E + 0.15∙A1 + 0.15∙A2, where E is the Exam grade, and A1 and A2 are grades for assignments.

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

Grossmann, W. and Rinderle-Ma, S., 2015. Fundamentals of Business intelligence. Springer.


From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.

Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.

Extensive FAQ's on MyStudymap can be found here.


Programme Co-ordinator: ms. Esme Caubo


There is only limited capacity for external students. Please contact the programme Co-ordinator
Important information about the course will be shared in Brightspace.