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Instructors: Kyra Ahrens; Dr. Muhammad Burhan Hafez
Event type:
Practical course/lab
Displayed in timetable as:
DAIS-Üb
Hours per week:
2
Language of instruction:
German/English
Min. | Max. participants:
- | 100
Comments/contents:
The practical course complements the lecture “Data-driven Intelligent Systems”. Students will elaborate the theoretical concepts and algorithms presented in the lecture with the aid of coding exercises performed in small groups. In addition, the interconnection between theory and application will be discussed both within the student groups as well as with the tutor.
Learning objectives:
The students work out current topics in the area of Data-driven Intelligent Systems. They learn to analyse complex interrelations between theory and practical applications, and will be motivated to transfer the gained knowledge to the exercises. Moreover, working in pairs as well as presentation of joint work and discussions with the tutor deepens soft skills such as teamwork and communication.
Didactic concept:
As part of the practical tutorials, programming assignments in python will be uploaded to an online course platform every other week, and students will have two weeks to complete them. Students are expected to arrange the necessary programming environment for the assignments on their own machines to enable completion of the assignments at home. Solutions to the assignments will be presented by selected groups, discussed and any questions will be answered during the (online) meeting held after each assignment due date every other week.
Prerequisite for passing the tutorials are the mandatory attendance and active participation in the biweekly assignment discussion meetings, the successful completion of the homework assignments, as well as an independent preparation and wrap-up of the lecture content essential for this purpose.
Teaching mode under COVID-19:
As far as the regulations of the University of Hamburg will allow it, we might do some of the assignment discussion meetings in person. However, further details cannot be given at this time due to the constantly changing pandemic situation. In any case, it will be possible to attend the assignment discussion meetings of the course "Data-driven Intelligent Systems" fully online.
Language:
The lecture is offered in English to give the participants a fair opportunity to gain experience with the standard language in science and engineering. We will offer the practical tutorials in English but are open to discuss individual matters in German to provide the best access for the participants. To this end, we will support the participants as best we can with both the language and the content.
Literature:
- Han J.; Kamber, M. Data Mining: Concepts and Techniques. Elsevier; Morgan Kaufmann, Amsterdam, 2006.
- Kantardzic, M. Data Mining. Wiley, 2011.
- Marsland, S. Machine Learning - An Algorithmic Perspective. CRC Press, 2015.
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