General Information
| Course Code | X_405086 |
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| Credits | 6 EC |
| Period | P2 |
| Course Level | 400 |
| Language of Tuition | English |
| Faculty | Faculty of Science |
| Course Coordinator | dr. D. Ceolin |
| Examiner | dr. D. Ceolin |
| Teaching Staff |
Z. Inayat dr. F. Ilievski dr. D. Ceolin |
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Part of programme(s)
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Practical Information
You need to register for this course yourself. The (de)registration deadlines can be found on VU.nl
The maximum number of students for this course is 120.
| Teaching Methods | Computer lab, Lecture |
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Target audiences
This course is also available as:
Course Objective
In this course, students will:
- Learn theory and methods concerning communication and interaction in a Web context (Knowledge and Understanding).
- Understand how user data is represented and distributed across devices in the context of the Social Web (Knowledge and Understanding).
- Apply the above skills in practical assignments (Apply Knowledge and Understanding).
- Reflect on social and ethical responsibilities linked to the application of these methods (Making Judgements).
- Communicate their knowledge and judgements in a final paper (Communication).
Course Content
This course will cover theory, methods and techniques for:
- personalization for Web applications;
- Web user & context modeling;
- user-generated content and metadata;
- multi-device interaction;
- usage of social-web data.
The course takes a data science approach, using Jupyter notebooks to collect and analyse data, with a research paper describing the data science study as the main outcome of the course.
Additional Information Teaching Methods
Lectures (1x week)Practical sessions (1x week)
Presentation seminars (1x week)
Method of Assessment
The weighted average of:
- 70% research paper (group assignment A),
- 10% group presentation (P),
- and 20% individual exam (E).
A minimum grade of 5.5 for each component is required.
Compensation: it is not possible to compensate one component with another.
Mode of re-examination: if insufficient, each component may be revised and resubmitted once.
Literature
- Course lecture slides;- Selected articles, videos and Web links
All materials for each lecture will be provided through Canvas.
Additional Information Target Audience
Master Artificial IntelligenceMaster Computer Science
Master Information Sciences
Master Computer Security
Additional Information
The course has a maximum enrolment limit of 120. The students of the Master Information Sciences, for whom it is compulsory, have priority over the students that take this course as an elective or a constrained choice course.
The students that take this course as an elective or a constrained choice course run the risk of not being able to participate, even if they have registered on time, if the maximum enrolment limit has been reached.
The students of the Master Information Sciences, for whom it is compulsory, run the risk of being initially refused if the enrolment limit has been reached at the time of registration. However this will be adjusted manually after registration has been closed so that all the students of the Master Information Sciences will be able to participate.