Universität Wien FIND

Bedingt durch die COVID-19-Pandemie können kurzfristige Änderungen bei Lehrveranstaltungen und Prüfungen (z.B. Absage von Vor-Ort-Lehre und Umstellung auf Online-Prüfungen) erforderlich sein. Melden Sie sich für Lehrveranstaltungen/Prüfungen über u:space an, informieren Sie sich über den aktuellen Stand auf u:find und auf der Lernplattform moodle.

Regelungen zum Lehrbetrieb vor Ort inkl. Eintrittstests finden Sie unter https://studieren.univie.ac.at/info.

Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.

180148 VO+UE Tools in Cognitive Science I: Computation, Computer-aided Methodologies and Problem Solving (2021W)

5.00 ECTS (3.00 SWS), SPL 18 - Philosophie
Prüfungsimmanente Lehrveranstaltung
VOR-ORT
Fr 08.10. 16:45-20:00 Hörsaal 2i NIG 2.Stock

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Freitag 15.10. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 22.10. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 05.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 12.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 19.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 26.11. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 03.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 10.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 17.12. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 07.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 14.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 21.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock
Freitag 28.01. 16:45 - 20:00 Hörsaal 2i NIG 2.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Different branches of digital sciences and computer science such as artificial intelligence, robotics, computational cognitive modelling, human-computer interaction, digital ethics, human-centric computing, etc., can be considered important (and even core) research fields of cognitive science. Analytical thinking and programming play fundamental roles in all these fields. Moreover, beyond their application in digital sciences and computer science, analytical thinking and programming are also widely used in other branches of cognitive science, such as the development of computer-based empirical experiments, data collection, data representation, data analysis, data visualisation, etc. Therefore, acquiring basic and working knowledge of analytical thinking and programming is essential for all cognitive science students.

This course introduces students to:
• basic concepts and challenges of digital sciences
• basic concepts of computation
• analytical, systemic and algorithmic thinking
• applied problem-solving skills
• working knowledge of programming (using Python), skills related to programming and application of programming in cognitive science
• practical skills related to design, implementation, and evaluation of computer-based empirical experiments, data collection, representation, analysis, visualisation, etc.
• basic understanding of the role of computer science in cognitive science
• basic understanding of human-centric approaches in computer science as well as cognitive science
• basic understanding of ethics and accountability in computer science as well as cognitive science

____ COVID 19 Updates ____

Considering the current developments related to COVID-19, the course will be held partially (or entirely) online (depending on the situation).

The decisions/updates and detailed instructions will be announced via Moodle platform or email.

Most of (or maybe all of) the communications, lectures, assignments, presentations, group-works, projects, evaluations, and exams will be done online.

– Course mode:
–– Mixed/hybrid (online + in-person) or fully online

– Teaching/learning methods:
– – Virtual/in-person synchronous course units,
– – Self-study with literature and online resources,
– – Virtual/in-person group-works,
– – Online/in-person exams,
– – Online/in-person presentations,
– – Virtual/in-person coaching/supervision sessions (if needed)
– – ...

– Students are expected to participate in announced online/in-person sessions, online/in-person presentations, online/in-person exams, etc.
– Students are expected to construct private virtual communication means for their virtual group works.
– Students are expected to regularly check their emails as well as the course Moodle environment.
– Students are expected to follow all detailed instructions related to remote/in-person teaching.
– The assessments will be based on the regular assessment plans.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The course will be graded on a basis of 100 points in total:• 100-87 points: Excellent (1)• 86-75 points: Good (2)• 74-63 points: Satisfactory (3)• 62-50 points: Sufficient (4)• 49-0 points: Unsatisfactory (5) (fail)

Mindestanforderungen und Beurteilungsmaßstab

Assessment criteria:• 10% Active participation• 25% Homework assignments (via Moodle)• 20% Presentation (debriefing) of homework assignments• 15% In-class quizzes• 15% Final Exam• 15% Final Project• A positive score (>50%) in each of the above criteria is required for passing the course.• Regular participation in at least 90% of sessions is obligatory.

Prüfungsstoff

Exam questions will be based on what we discuss in class, the readings and the homework assignments.

Literatur

https://www.python.org/doc/• Further readings will be announced in the course

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 01.09.2021 11:08