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Elective Course: Business Intelligence and Big Data Analysis

Computer Science / Informatics / Mathematical Computer Modelling
master course
Teaching language

Tilmelding sker via STADS-Selvbetjening indenfor annonceret tilmeldingsperiode, som du kan se på Studieadministrationens hjemmeside

Når du tilmelder dig kurset, skal du være opmærksom på, om der er sammenfald i tidspunktet for kursusafholdelse og eksamen med andre kurser, du har valgt. Uddannelsesplanlægningen tager udgangspunkt i, at det er muligt at gennemføre et anbefalet studieforløb uden overlap. Men omkring valgfrie elementer og studieplaner som går ud over de anbefalede studieforløb, kan der forekomme overlap, alt efter hvilke kurser du vælger.

Registration through STADS-Selvbetjeningwithin the announced registration period, as you can see on the Studyadministration homepage.

When registering for courses, please be aware of the potential conflicts between courses or exam dates on courses. The planning of course activities at Roskilde University is based on the recommended study programs which do not overlap. However, if you choose optional courses and/or study plans that goes beyond the recommended study programs, an overlap of lectures or exam dates may occur depending on which courses you choose.

Detailed description of content

Data is being collected, analyzed, and used in intelligent applications as never before. This applies across all areas of business, science and life. We live in an age not only of a digital revolution, but also of a data revolution, where businesses, in order to succeed, need to be ever more data-driven. But what does it mean to be data-driven and what are Big Data, Machine Learning, Artificial Intelligence, and Data Science in a business context? In this course, we will answer these questions by giving a hands-on introduction to Data Science (using the tool R) looking at how data can be utilized especially within businesses and organizations. We will discuss classical Business Intelligence and how data can be utilized in solving business problems. We will look at the entire data analysis cycle: from asking questions, collecting, preprocessing, and analyzing data, to building (machine learning) models and communicating the results. Furthermore, we will look at the particular challenges of storage and computation in the context of Big Data.

Expected work effort (ects-declaration)

The course will have a total workload of 135 hours with 40 hours of lectures and exercises, 70 hours of preparation over an 11 week course period and 25 hours for the exam and preparation before the course

Course material and reading list

Articles and extracts from books and web.

Evaluation- and feedback forms

There will be feedback on exercises which are set during the course. An evaluation will take place at the end of the course

Administration of exams
IMT Studieadministration (imt-studieadministration@ruc.dk)
Responsible for the activity
Henrik Bulskov (bulskov@ruc.dk)
Jesper Schmidt Hansen (jschmidt@ruc.dk)
Jens Ulrik Hansen (jensuh@ruc.dk)
Type of examination

Individual oral examination based on a set assignment.

The examination is conducted as a dialogue. During the examination, questions can be asked regarding the entire syllabus. The written product must be between 4,800 - 48,000 characters in length, including spaces.

The size specifications include the cover, table of contents, bibliography, figures and other illustrations, but exclude any appendices. Time allowed for examination including time used for assessment 20 minutes. The assessment is an overall evaluation of the written product and the oral examination. Permitted support and preparation materials during the examination: All.

Assessment: 7-point grading scale. Moderation: Internal co-assessor.


Same as ordinary

Learning outcomes and assessment criteria
  • Knowledge and understanding of a specific subject area in computer science

  • Knowledge and understanding of the area’s techniques for designing and constructing software systems that meet specific requirements

  • Knowledge and understanding of the general principles behind the subject area’s theory, methods and technological solutions.

Skills in electing and applying appropriate methods and techniques from the subject area in order to analyse, design and construct reliable and user-friendly software systems

  • Competences in being able to work on computer science-related issues, both independently and in teams

  • Competences in being able to become proficient in new approaches to the subject area in a critical and systematic way and thereby independently take responsibility for one’s own professional development.

Overall content

With an elective course, the student has the opportunity to specialise in a specific subject area where the student acquires knowledge, skills and competences in order to translate theories, methods and solutions ideas into their own practice in relation to software development.

Examples of elective courses: Robotics, AI, internet technologies, programming language, parallel calculation, mobile computers, etc.The specific contents are listed on study.ruc.dk.

Prerequisites for participation
Currently no data from curriculum.
Prerequisites for participation in the exam
Currently no data from curriculum.
Teaching and working methods

Normal class instruction, i.e. a mix of lecturer presentations, student presentations and practical work on specific tasks.

Lecture with exercises.

Is stated in the description on study.ruc.dk.

Type of course

Elective course

Exam code(s)
Exam code(s) : U40549
Last changed 14/02/2020

lecture list:

Show lessons for Subclass: 1 Find calendar (1) PDF for print (1)

Monday 10-02-2020 12:15 - 10-02-2020 16:00 in week 07
Informatics: Business Intelligence and Big Data (BIBA)

Monday 17-02-2020 12:15 - 17-02-2020 16:00 in week 08
Informatics: Business Intelligence and Big Data (BIBA)

Monday 24-02-2020 12:15 - 24-02-2020 16:00 in week 09
Informatics: Business Intelligence and Big Data (BIBA)

Monday 02-03-2020 12:15 - 02-03-2020 16:00 in week 10
Informatics: Business Intelligence and Big Data (BIBA)

Monday 09-03-2020 12:15 - 09-03-2020 16:00 in week 11
Informatics: Business Intelligence and Big Data (BIBA)

Monday 16-03-2020 12:15 - 16-03-2020 16:00 in week 12
Informatics: Business Intelligence and Big Data (BIBA)

Monday 23-03-2020 12:15 - 23-03-2020 16:00 in week 13
Informatics: Business Intelligence and Big Data (BIBA)

Monday 30-03-2020 12:15 - 30-03-2020 16:00 in week 14
Informatics: Business Intelligence and Big Data (BIBA)

Monday 06-04-2020 12:15 - 06-04-2020 16:00 in week 15
Informatics: Business Intelligence and Big Data (BIBA)

Monday 20-04-2020 12:15 - 20-04-2020 16:00 in week 17
Informatics: Business Intelligence and Big Data (BIBA)

Monday 27-04-2020 10:00 - 27-04-2020 10:00 in week 18
Informatics: Business Intelligence and Big Data (BIBA) - Hand in

Monday 08-06-2020 08:15 - Tuesday 09-06-2020 18:00 in week 24
Informatics: Business Intelligence and Big Data (BIBA) - Oral exam

Wednesday 05-08-2020 10:00 - 05-08-2020 10:00 in week 32
Informatics: Business Intelligence and Big Data (BIBA) - Reexam hand in

Monday 17-08-2020 08:15 - 17-08-2020 18:00 in week 34
Informatics: Business Intelligence and Big Data (BIBA) - Oral Reexam