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317.547 Machine Learning in Engineering Applications
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022S, SE, 2.0h, 2.0EC

Properties

  • Semester hours: 2.0
  • Credits: 2.0
  • Type: SE Seminar
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to...

  • students are able to collect information on a topic selected from a pool of predefined topics in the field of machine learning by studying the literature, using the internet or contacting companies
  • summarize topic-specific information in a structured way in an English-language manuscript
  • compile a presentation in English on the selected topic
  • give a presentation of about 20 minutes in English on the chosen topic to the students enrolled in the seminar
  • discuss the content of the presentation with the students of the seminar in English
  • to participate in professional discussions in English as a participant in the seminar

Subject of course

Machine learning refers to computer algorithms that can improve independently through experience. Machine learning algorithms build a model based on sample data called "training data" to make predictions or decisions without being explicitly programmed to do so. With increasingly powerful resources for storing and processing data, these algorithms have also found their way into mechanical engineering. This seminar will provide an overview of the application of these algorithms.

Specific machine learning approaches in mechanical engineering will be summarized by the seminar participants in the form of independent contributions under expert supervision of the institute, elaborated as manuscript and presentation, presented and discussed. The participants can choose from an annually changing list of topics.

Teaching methods

After the selection of the individual topics, students are supported in finding suitable literature. Questions regarding content, preparation and presentation are possible at any time via e-mail or during office hours. The manuscript will be sent to the lecturer via e-mail one day before the presentation and uploaded by her for all participating students. Following the presentation, students will be invited to discuss the presentation. The quality of the presentation will be discussed by and with the students, questions will be asked about the content and subject matter, and the students discuss new insights that they have gained from this presentation. Participation in the discussion and attendance will be included in the grade.

Mode of examination

Immanent

Additional information

The seminar is expected to take place in person. If required by external circumstances, it can be transformed into an online format.

Please consider the plagiarism guidelines of TU Wien when writing your seminar paper: Directive concerning the handling of plagiarism (PDF)

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon10:00 - 12:0007.03.2022 - 27.06.2022GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Machine Learning in Engineering Applications - Single appointments
DayDateTimeLocationDescription
Mon07.03.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon14.03.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon21.03.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon28.03.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon04.04.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon25.04.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon02.05.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon09.05.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon16.05.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon23.05.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon30.05.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon13.06.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon20.06.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine
Mon27.06.202210:00 - 12:00GM 7 Kleiner Schiffbau Besprechungs- und Vortragstermine

Examination modalities

The final grade will be composed of evaluations of the manuscript and presentation as well as participation in the discussion and attendance.

Course registration

Begin End Deregistration end
01.02.2022 09:00 30.06.2022 17:00 30.06.2022 17:00

Curricula

Literature

No lecture notes are available.

Language

English