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prevented to attend the inspection on February 14th, this must be announced in good time on the bulletin board (Schwarzes Brett). Students who would like to view their exam then have the opportunity to request [...] stated. In order to meet deadlines, inspection must be possible within four calendar weeks from the day the grades are announced. The agreed appointment must be observed, there is no right to catch up on [...] und Erstkorrektor- innen. The inspection will take place on Friday, February 14th, 2025, from 9:00 to 12:00 at the MBUT Faculty with the respective first correctors 2. Sollten Erstkorrektoren

Institute of Applied Language Studies City Center Tour – from UWB campus to Brewery Pilsner Urquell Brewery Tour Dinner Departure to Amberg Wednesday June 4th Day 3 Amberg + Weiden, Germany [...] Workshop “Vitality for Performance” by Prof. Jan von Zwieten Trip to Weiden Campus Tour, Social Event KOMOpivo (Beer tasting) Departure to Amberg page Czech-German Staff Week 2025 [...] AW, UWB + EUPeace Alliance Participants’ presentations of their institutions Coffee Break and Meeting with faculty representatives Campus Tour and City Center Tour Dinner Tuesday June 3rd

Institute of Applied Language Studies City Center Tour – from UWB campus to Brewery Pilsner Urquell Brewery Tour Dinner Departure to Amberg Wednesday June 4th Day 3 Amberg + Weiden, Germany [...] Workshop “Vitality for Performance” by Prof. Jan von Zwieten Trip to Weiden Campus Tour, Social Event KOMOpivo (Beer tasting) Departure to Amberg page Czech-German Staff Week 2025 [...] AW, UWB + EUPeace Alliance Participants’ presentations of their institutions Coffee Break and Meeting with faculty representatives Campus Tour and City Center Tour Dinner Tuesday June 3rd

forschung Studi-Kino Studi-Kino Studi-Kino Kirschblüten- festival Speed Meeting Billiard & Dart Good to Know 8. April Bewerbungsworkshop AM 9. April Bewerbungsworkshop WEN 29. April [...] page Bierpong- Stammtisch Opening Party Studieninfotag Studikino Ersti-Tag Good to Know 20. März Medieninfotag 24.-27. März Vorverkauf Opening 10 17 24 31 11 18 [...] Studi Kino Studi-Kino Studi-Kino Start Prüfungs- anmeldung Careerday Weiden Good to Know 21. Mai Simulierte Vorstellungsgespräche mit Wirtschaftsjunioren 5 12 19 26 6

designed to enable students to take on a leading role in groups or organisations and to promote the professional development of team members in a targeted manner. 2Students should learn to define goals [...] independently, use suitable means to achieve them and accompany detailed project planning and implementation. 3One of the aims of the degree programme is to be able to recognise, assess and deal with [...] 2At the same time, students learn how to systematically consider the social, cultural, ecological and ethical effects of activities and decisions, subject them to critical reflection and incorporate

vehicles is extended by a multi-agent reinforcement learning approach in order to be able to control several vehicles (fleet). Using simple examples and an existing solver for the so-called Dial-A-Ride problem [...] eines Multi-Agent Reinforcement Learning Ansatzes zur Steuerung von Fahrzeugflotten Zusammenfassung: Nach Literaturanalyse wird ein bestehender Reinforcement Learning Ansatz zur Steuerung von Fahrzeugen [...] t of a multi-agent reinforcement learning approach for controlling vehicle fleets Summary: After analyzing the literature, an existing reinforcement learning approach for controlling vehicles

work on real-life projects, and profit from virtual and in situ input sessions. They will learn to cooperate in teams and create goal-driven solutions. • We will encourage ‘thinking outside [...] project management and teamwork, and a multitude of advisors and helpers come together to learn, experience, share, and implement sustainability concepts. 50:50 Equal focus on theory and [...] Summer School on Sustainability 2025 We look forward to receiving your application for the ISSS 2025! Apply now Go to oth-aw.de/isss and submit your application 10

Verfahren (z.B. XAI, Embedded AI, semi-/self-supervised learning, active learning, federated learning, contrastive learning, transfer learning, DL für Audiosignale) Lehrmaterial / Literatur Teaching [...] Practical Machine Learning Tools and Techniques, Morgan Kaufmann, 2018. A. Géron: Hands-on Machine Learning with Scikit-Learn, Keras and Tensor Flow, O’Reilly, 2018 Raschka: Machine Learning mit Python: das [...] and Machine Learning, Springer, 2006. F. Chollet: Deep Learning with Python, Manning, 2018. (deutsche Version bei mitp Professional, 2018) A. Géron: Hands-On Machine Learning with Scikit-Learn, Keras, and

science and the machine learning domain • Understanding some of the most widely used machine learning methods • Being able to implement a machine learning pipeline in order to solve real world problems [...] Voraussetzungen* Prerequisites This course is an introduction to ML. There is no need to have any prior knowledge about machine learning *Hinweis: Beachten Sie auch die Voraussetzungen nach Prüf [...] limited to linear regression and classification, Support vector machines and Deep neural networks. 3) Introduction to Python programming for data science. 4) Applying machine learning models on

BYCZ 01- 100). The aim of the project is to set up, pilot, evaluate and successfully implement a new, unique study programme focused on applied learning that is of great importance for the Bava [...] partnership between OTH Amberg-Weiden and the University of West Bohemia Intensified practical learning with two internships facilitated by the universities Unique programme in both Bavaria and the [...] Bavarian-Czech border region. With a total budget of 411,001.25 Euro, the project runs from May 1, 2024 to February 28, 2027. FIND OUT MORE 2 Bachelor degrees (B.Sc. and Bc.) in one programme 8

Industrial Property Law IB Übungsleistung Christian Stauf Introduction to Academic Research IB Projektarbeit Anna Grimm Meetings, Negotiations & Conflict IB Übungsleistung Saeid Matinfar MS Office Experts [...] Examination inspection: to be announced 4. Please note: - You will not receive a grade without exam registration during the examination registration in Primuss! This also applies to repeat examinations [...] the semester. - Anyone who notices overlaps in examinations to be taken must report this immediately, at the latest by 17.12.2024 to Ms. Trottmann (f.trottmann@oth-aw.de) - In individual cases,

(7) In addition to specialist and methodological skills, the degree programme aims to convey the joy of learning and the creative application of knowledge, promote the ability to criticise and reflect [...] language skills in the first two study sections to enable them to enter the German labour market at the start of the practical semester and to be able to complete the third study section partly in German [...] deemed to have been taken for the first time and failed. (2) 1 Entry to the third stage of the programme requires that all modules of the first stage of the programme have been passed. 2In order to ensure

has to checked individually. details to be specified in the first semester the module is taught 150h, details to be specified in the first semester the module is taught Learning Outcomes [...] Methodological skills:  Ability to program algorithms for IoT applications  Ability to develop software projects in IoT environment  Ability to implement sensors and actuators using libraries [...] Type/Scope incl. Weighting *2) Learning Objectives/ Competencies to be Assessed Written Exam (Kl90) Written Exam, 90 minutes Written Exam (Kl90) *1) Please refer to the applicable overview

Filmmaker’s Eye: Learning (and Breaking) the Rules of Cinematic Composition. Focal Press, New York · Riley, C. (2009): The Hollywood Standard. The Complete and Authoritative Guide to Script Format and [...] E.R. (2017): Computer Vision: Principles, Algorithms, Applications, Learning. Academic Press · Eck, D.J. (2018): Introduction to Computer Graphics. Online-Ressource · Eckardt, M. (2016): Cinema 4D 18 [...] source · Goodfellow, I., Bengio, Y., & Courville, A. (2016): Deep Learning. MIT Press · Kaehler, A. & Bradski, G. (2016): Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library. O'Reilly Media

Filmmaker’s Eye: Learning (and Breaking) the Rules of Cinematic Composition. Focal Press, New York · Riley, C. (2009): The Hollywood Standard. The Complete and Authoritative Guide to Script Format and [...] E.R. (2017): Computer Vision: Principles, Algorithms, Applications, Learning. Academic Press · Eck, D.J. (2018): Introduction to Computer Graphics. Online-Ressource · Eckardt, M. (2016): Cinema 4D 18 [...] source · Goodfellow, I., Bengio, Y., & Courville, A. (2016): Deep Learning. MIT Press · Kaehler, A. & Bradski, G. (2016): Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library. O'Reilly Media

h Übungsleistungen: 70 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Klausurvorbereitung: 30 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Klausurvorbereitung: 30 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden

h Übungsleistungen: 70 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Klausurvorbereitung: 30 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Klausurvorbereitung: 30 h Gesamtaufwand: 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden

/Pipher, J./Silverman, J. H. (2014): An Introduction to Mathematical Cryptography, 2. Auflage, Springer · Katz, J./Lindell, Y. (2015): Introduction to Modern Cryptography, 2. Auflage, CRC Press · Lipton [...] Synthese gesprochener Sprache (text-to-speech) · Sprachdialogsysteme · Textanalyse, Dokumentanalyse, OCR · Clustering/Klassifikation · Neuronale Netze und Deep Learning Lehrmaterial/Literatur Teaching [...] Vor-/Nachbereitung: 45 h PrA: 45 h Gesamt: 150 h Lernziele/Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden

/Pipher, J./Silverman, J. H. (2014): An Introduction to Mathematical Cryptography, 2. Auflage, Springer · Katz, J./Lindell, Y. (2015): Introduction to Modern Cryptography, 2. Auflage, CRC Press · Lipton [...] Synthese gesprochener Sprache (text-to-speech) · Sprachdialogsysteme · Textanalyse, Dokumentanalyse, OCR · Clustering/Klassifikation · Neuronale Netze und Deep Learning Lehrmaterial/Literatur Teaching [...] Vor-/Nachbereitung: 45 h PrA: 45 h Gesamt: 150 h Lernziele/Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden

true Author Andrea Bäuml producer Microsoft: Print To PDF access_permission:can_modify true pdf:docinfo:producer Microsoft: Print To PDF pdf:docinfo:created 2025-01-17T10:56:59Z ME_Pr [...] hweis ME Innovationsmanagement Steinhauser semesterbegleitender Leistungsnachweis ME Machine Learning for Engineers Götz semesterbegleitender Leistungsnachweis ME Maschinelles Sehen und Mustererkennung

Examination inspection: to be announced 4. Please note: - You will not receive a grade without exam registration during the examination registration in Primuss! This also applies to repeat examinations [...] the semester. - Anyone who notices overlaps in examinations to be taken must report this immediately, at the latest by 17.12.2024 to Ms. Trottmann (f.trottmann@oth-aw.de) - In individual cases, [...] Management IMS/DEI Übungsleistung Fischer MS Office Experts IB/IMS Übungsleistung Jawadur Rahman Service Learning IMS Projektarbeit Ranisch Social Entrepreneurship & Sustainable Innovation IMS Präsentation Löbus

des Workload According to § 8 para. 1 sentence 3 BayStudAkkV, the following applies: One credit point is based on a workload of 25 to 30 hours. To calculate the workload, a distinction [...] preparation and follow-up of the learning material • Exam preparation = hours spent preparing for an examination event • Examination workload = hours required to complete the examination • [...] university must be submitted to the Students` Office after enrollment at OTH. Subsequently, the respective lecturers will check whether the subjects already taken correspond to the requirements of our subjects

L Labor laboratory/ lab Laborordnung laboratory regulations Lernportfolio Learning Portfolio M Medienproduktion und Medientechnik Media Production and Media Technology [...] atik Media Informatics page Präsentation presentation Präsenzveranstaltung face-to-face class Praxisphase internship phase Professor professor Projektarbeit Project [...] Prüfungsordnung examination regulations Prüfungsunfähigkeitsbescheinigung certificate of inability to take exams R Regelstudienzeit standard period of study Rückmeldung reregistration

Zusammenhang mit Energiespeicherung (Wasserstoff, Elektrolyse, Brennstoffzellen, power to gas, power to liquid, biomass to liquid, CARNOT-Batterie, adiabate Druckluft etc.), Flexibilisierung von Kraft-Wä [...] Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die [...] Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die

Zusammenhang mit Energiespeicherung (Wasserstoff, Elektrolyse, Brennstoffzellen, power to gas, power to liquid, biomass to liquid, CARNOT-Batterie, adiabate Druckluft etc.), Flexibilisierung von Kraft-Wär [...] Nachbereitung Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Nachbereitung Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden