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Data & Things

Data & Things
Master programme in
Computer Science
Type of activity


Teaching language
Study regulation

Read about the Master Programme and find the Study Regulations at ruc.dk


Sign up for study activities at STADS Online Student Service within the announced registration period, as you can see on the Study administration homepage. When signing up for study activities, please be aware of potential conflicts between study activities or exam dates. The planning of 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.

Number of participants
Responsible for the activity
Jens Ulrik Hansen (jensuh@ruc.dk)
Hua Lu (luhua@ruc.dk)
Head of study
Henrik Bulskov (bulskov@ruc.dk)
Study administration
IMT Registration & Exams (imt-exams@ruc.dk)
Exam code(s)
Overall objective

Advanced data solutions and complex device systems.

Detailed description of content

This course focuses on building data centric applications that utilize data to create new insights or features. In doing this, we need to understand how to analyze data and create statistical and machine learning models, as well as learning how to process, transform, and manage data. In managing data, we will go beyond the classical relational databases and cover topics such as parallel and distributed data systems, partial and graph databases, and data from IoT devices. Moreover, we will cover how to put data products, such as machine learning models, into production and monitor their performance (ML Ops). Thus, this course cover both hands-on introductions to data science, machine learning, data engineering, ML Ops, as well as building complex data centric systems that may utilize IoT devices and external data sources as input to statistical and machine learning models that may result in visualizations, features, or effects into the environment.

Course material and Reading list

Will be announced on Moodle.

Overall plan and expected work effort

The course will have a total workload of 275 hours.

Evaluation and feedback

Evaluation form to be filled out (anonymously) plus open discussion on the last course day

Overall learning outcomes

After completing this activity, students will be able to:

  • analyse, implement, and verify complex data solutions to solve problems within complex IT systems.

  • demonstrate knowledge of modern data storages, and data engineering and science.

  • understand and implement solutions that integrate computation into the environment and use serval devises and systems.

  • design and implement coordination for systems with many software and hardware components and interfaces suitable for ubiquitous computing.

Form of examination
Individual oral exam based on a written product..

The character limit of the written product is maximum 48.000 characters, including spaces.
The character limits include the cover, table of contents, bibliography, figures and other illustrations, but exclude any appendices.

Time allowed for exam including time used for assessment: 20 minutes.
The assessment is an overall assessment of the written product(s) and the subsequent oral examination.

Permitted support and preparation materials for the oral exam: All.

Assessment: 7-point grading scale.
Moderation: Internal co-assessor.
Form of Re-examination
Samme som ordinær eksamen / same form as ordinary exam
Type of examination in special cases
Examination and assessment criteria


Exam code(s)
Exam code(s) : U60058
Last changed 06/03/2023

lecture list:

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

Thursday 02-02-2023 08:15 - 02-02-2023 16:00 in week 05
Data & Things (COMP)

Monday 06-02-2023 08:15 - 06-02-2023 16:00 in week 06
Data & Things (COMP)

Wednesday 08-02-2023 08:15 - 08-02-2023 16:00 in week 06
Data & Things (COMP)

Friday 10-02-2023 08:15 - 10-02-2023 12:00 in week 06
Data & Things (COMP)

Monday 13-02-2023 08:15 - 13-02-2023 16:00 in week 07
Data & Things (COMP)

Wednesday 15-02-2023 08:15 - 15-02-2023 16:00 in week 07
Data & Things (COMP)

Friday 17-02-2023 08:15 - 17-02-2023 12:00 in week 07
Data & Things (COMP)

Monday 20-02-2023 08:15 - 20-02-2023 12:00 in week 08
Data & Things (COMP)

Wednesday 22-02-2023 08:15 - 22-02-2023 16:00 in week 08
Data & Things (COMP)

Friday 24-02-2023 08:15 - 24-02-2023 12:00 in week 08
Data & Things (COMP)

Monday 27-02-2023 08:15 - 27-02-2023 12:00 in week 09
Data & Things (COMP)

Wednesday 01-03-2023 08:15 - 01-03-2023 16:00 in week 09
Data & Things (COMP)

Friday 03-03-2023 08:15 - 03-03-2023 12:00 in week 09
Data & Things (COMP)

Thursday 23-03-2023 10:00 - 23-03-2023 10:00 in week 12
Data & Things - Hand-in (COMP)

Tuesday 28-03-2023 08:15 - Wednesday 29-03-2023 18:00 in week 13
Data & Things - Oral examination (COMP)

Monday 07-08-2023 10:00 - 07-08-2023 10:00 in week 32
Data & Things - Reexam - Hand-in (COMP)

Friday 11-08-2023 08:15 - 11-08-2023 18:00 in week 32
Data & Things - Oral reexamination (COMP)