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raining). General Information • Subscribe to the Noticeboard. • Subscribe to the Moodle announcements for each course. • Make sure to obtain your A2 certificate as soon as possible! [...] • To enter Study Section 2 (Semesters 6–7), you must have: o Passed the modules from Semesters 1–3 o Earned at least 120 ECTS out of 150 from Semesters 1–5 • Specific prerequisite to note early: [...] possible with valid reason). • To register a thesis topic, you must first complete 30 experimental hours as a participant in approved studies. Start early to collect these hours and obtain the

programme is to enable students to act and to independently and autonomously learn and apply scientific knowledge and methods in the fields of Artificial Intelligence (AI), Machine Learning (ML) as [...] ²They are qualified to work on application or research-oriented tasks and projects in a scientifically sound and largely independent manner. ³They have learned to define goals, to develop knowledge [...] international business. ³They learn how to deal with English in a business-fluent manner. ⁴They thus meet the requirements of international business and are prepared to take on responsibility and

Learning objectives/competencies to be assessed Zu prüfende Lernziele/Kompetenzen ModA Learning objectives / qualifications of the module, see above *1) Please refer to the [...] They learn to identify these situations and to appear interculturally competent. • Personal competence (social competence and self-competence): Students acquire the interdisciplinary ability to perform [...] ns and experiences in order to promote learning from both mistakes and successes. Despite the obligation to deliver a usable product, the focus is on independent learning (from mistakes as well as from

9Z 2510_OTH-meets-Fraunhofer.indd page Take the chance to join this event! When: Oktober 28, 2025 – 15.30 to 16.15 CET: Introduction of Fraunhofer UMSICHT – 16.15 to 17.15 CET: Speed [...] pdf:PDFVersion 1.3 xmp:CreatorTool Adobe InDesign 20.5 (Windows) pdf:docinfo:title 2510_OTH-meets-Fraunhofer.indd stream_content_type application/pdf pdf:hasXFA false access_permission:c [...] 20.5 (Windows) access_permission:fill_in_form true pdf:encrypted false dc:title 2510_OTH-meets-Fraunhofer.indd xmp:CreateDate 2025-10-08T11:40:49Z modified 2025-10-08T09:40:58Z pdf:ha

(Full-Time) *Electives change each semester. You need to complete 3 in total. 1. Compulsory Modules 30 24 15 12 0 0 1.1 Deep Learning (DPLE) 5 4 1.2 Computer Vision and AI (CVAE) [...] 5 4 1.3 Autonomous Robots (AURE) 5 4 1.4 Machine Learning (MALE) 5 4 1.5 Modern Databases and NoSQL (MDNE) 5 4 1.6 NPL and Information retrieval (NLPE) 5 4 1.7 AI

*Electives change each semester. You need to complete 3 in total. 1. Compulsory Modules 10 8 15 12 10 8 10 8 0 0 1.1 Deep Learning (DPLE) 5 4 1.2 Computer Vision and AI [...] AI (CVAE) 5 4 1.3 Autonomous Robots (AURE) 5 4 1.4 Machine Learning (MALE) 5 4 1.5 Modern Databases and NoSQL (MDNE) 5 4 1.6 NPL and Information retrieval

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

ce): The students are able to combine knowledge and skills from the basic modules to derive and develop new solutions. The have the competence to discuss issues related to energy storage in interdisciplinary [...] Psychological Association. The Official Guide to APA Style (7th Ed.) Washington. Carlson, K. A. & Winquist, J. R. (2017). An Introduction to Statistics. An Active Learning Approach. SAGE. Creswell, J. W. & Plano [...] Ability to recognise legal problems in energy/environmental law, identification of the most important applicable regulations Independent application of regulations relevant to practice Ability to identify

Environmental Engineering There is no entitlement to all compulsory elective modules and elective modules being offered. Similarly, there is no entitlement to courses being offered if the number of participants [...] Technology 5 4 3.2.2 Digital Signal Processing 5 4 3.2.3 PLC-Programming 5 4 3.2.4 Machine Learning 5 4 3.2.5 Energy Conversion in Power/Working Machines 5 4 3.2.6 Smart Grids 5 4 3.3.1 Rheology

we invite practitioners to share the practices they are already implemeting to make their businesses more just and sustainable. Let others know about your successes, meet likeminded people from [...] will serve as a platform to explore viable paths and opportunities for collaboration, bringing together researchers, practitioners, policymakers, and industry leaders to drive transformative change [...] from all disciplines and sectors (academic, public, private, and civil society) related to, but not limited to, the following topics: • Economic systems and the common good • Theoretical foundations

the first few weeks of your studies. We can give you the answers to everything that's still unclear to you! Please register by e-mail to sdc@oth-aw.de. 2. Präsenzworkshop zu Resilienz und Studi [...] Rest Everyone Needs Dec 2, 2025, 4-5.30pm: Managing Social Anxiety Dec 9, 2025, 4-5.30pm: Learning to Learn Effectively Dec 16, 2025, 6-7.30pm: Beating Loneliness as a Student Jan 13, 2026, 4-5.30pm: [...] workshop, you'll find space for reflection, new ideas, and tips to ensure that your studies remain on track. Please register by e-mail to sdc@oth-aw.de. annotation mailto:sdc@oth-aw.de mailto

Master Thesis Reinforcement Learning: Fine-tuning Pretrained Policies with Real-World Data to Mitigate the Sim-to-Real Gap Summary The performance of reinforcement learning policies is highly dependent [...] world, a domain shift occurs, leading to degraded performance. This performance loss is known as the sim-to-real gap, and the goal of this thesis is to reduce it. To achieve this, a policy pretrained in [...] reinforcement learning is a plus We offer • Individual supervision and regular feedback to support your growth in reinforcement learning • Participation in current research projects • Freedom to choose

reinforcement learning is a plus We offer: - Individual supervision and regular feedback to support your growth in reinforcement learning - Participation in current research projects - Freedom to choose the [...] performance. This performance loss is known as the sim-to-real gap , and the goal of this thesis is to reduce it. To achieve this, a policy pretrained in simulation will be fine-tuned using real-world data. The [...] Conduct a literature review on fine-tuning reinforcement learning policies online - Develop and build an AI model to fine-tune a reinforcement learning policy - Deploy the model on an edge device such as the

introduction to object-oriented programming, including an overview of the language syntax and how to develop simple applications. Students will learn how to write custom classes and methods, and how to test their [...] Learning Objectives/Competencies to be Assessed Module work (ModA) Project Work in Groups 50% Presentation, similar to board presentation at annual shareholder meeting 50% written [...] weighting *2) Learning Objectives/Competencies to be Assessed Module work (ModA) Project Work in Groups The group project is used to test the practical learning content and competence profiles

true Author Michael Wiehl producer Microsoft: Print To PDF access_permission:can_modify true pdf:docinfo:producer Microsoft: Print To PDF pdf:docinfo:created 2025-10-22T13:40:25Z Studienplan [...] Deep Learning (DPLE) 4 5 4 5 1.2 Computer vision and AI (CVAE) 4 5 4 5 1.3 Autonomous robots (AURE) 4 5 4 5 0 0 AI basics data & language (winter) 0 0 12 15 0 0 12 15 17% 2.1 Machine Learning (MALE)

Environmental Engineering There is no entitlement to all compulsory elective modules and elective modules being offered. Similarly, there is no entitlement to courses being offered if the number of participants [...] Technology 5 4 3.2.2 Digital Signal Processing 5 4 3.2.3 PLC-Programming 5 4 3.2.4 Machine Learning 5 4 3.2.5 Energy Conversion in Power/Working Machines 5 4 3.2.6 Smart Grids 5 4 3.3.1 Rheology

also be an HR session to present entry-level and career opportunities. This will give you the opportunity to meet HR managers in person. Don't miss this chance! We will travel to both companies by bus [...] bus. Everything is free of charge. We will meet in front of the OTH cafeteria for departure. We will also return to the OTH. Kind regards ... Vielen Dank und schöne Grüße Fabian Liedl [...] Dear students, please register for the excursions to ZMS in Schwandorf and Siemens in Amberg via https://www.oth-aw.de/en/myoth/ . You can find the excursions in the excursion portal. Destination: ZMS

system Examination boards Learning spaces Insurances You are here: Studies Getting started University formalties Info session: Exam registration and study organization In addition to revising for exams, success [...] from Wednesday, 10th December 2025 to Wednesday, 7th January 2026 inclusive . (Please note: MANDATORY exam registration for all). All deadlines and dates related to exams can be found on the website ( [...] lecture-free periods Examinations Examinations Repeat examinations Examination system Examination boards Learning spaces Insurances University formalties Overview Info session: Exam registration and study organization

• Raschka, S., Liu, Y. H., & Mirjalili, V. (2022). Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python. Packt Publishing Ltd. • Goodfellow [...] lineare Regression mit scikit-learn • Einführung in Deep Learning - Grundprinzipien neuronaler Netze (Feedforward, Training, Overfitting) - Erstellung einfacher Deep-Learning-Modelle mit Keras oder PyTorch [...] Material / Reading • Géron, A. (2022). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. " O'Reilly Media, Inc.". •

Ivanov, Dmitry (2024): Digital Supply Chain Management and Technology to Enhance Resilience by Building and Using End-to-End Visibility During the COVID-19 Pandemic. In: IEEE Trans. Eng. Manage. [...] Roming, Lukas; Franke, Jörg; Reitelshöfer, Sebastian (2025b): The path to a more efficient circular economy by integrating deep learning into robotic sorting system. In: Global Conference on Sustainable [...] Bernt Mayer 24 A Micro Data Approach to the Identification of Credit Crunches von Timo Wollmershäuser und Horst Rottmann 25 Strategies and possible directions to improve Technology Scouting in

Machine Learning mit Scikit-Learn, Keras und TensorFlow“, O'Reilly; 2. Edition (2020) Bishop, C.M.: „Pattern Recognition and Machine Learning“, Springer (2006) Chollet, F.: „Deep Learning with Python“ [...] Seite 66 von 86 4.1.3 Machine Learning for Engineers – Einführung in Methoden und Werkzeuge Machine Learning for Engineers – Introduction to Methods ans Tools Zuordnung zum Curriculum [...] und verschiedener Algorithmen des Machine Learning. • Methodenkompetenz: Die Studierenden sind befähigt, verschiedene Verfahren des Machine Learnings praktisch anzugehen und die Ergebnisse zu

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 [...] 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 [...] Nachbereitung Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden [...] Selbststudium Prüfungsvorbereitung = 90 h = 150 h Lernziele / Qualifikationen des Moduls Learning Outcomes Nach dem erfolgreichen Absolvieren des Moduls verfügen die Studierenden über die folgenden

Zusammenhang mit Energiespeicherung (Wasserstoff, Elektrolyse, Brennstoffzellen, power to gas, power to liquid, biomass to liquid, etc.), Flexibilisierung von Kraft-Wärme-Kälte-Kopplungsprozessen durch die [...] 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

machine learning. • Methodological competence: The students are able to practically apply various machine learning methods and to evaluate the results. • Personal competence: Ability to discuss [...] Personal competence: Ability to communicate about lightweight engineering; ability to work independently as well as in team to solve a technical problem; ability to lifetime learning Course Content Inhalte [...] private situations. They learn to identify these situations and to appear interculturally competent. • Personal competence: Students acquire the interdisciplinary ability to perform in a culturally