DI Dr. techn. Mugdim Bublin Academic Staff Stadt Wien Endowed Professorship for Artificial Intelligence mugdim.bublin@fh-campuswien.ac.at T: +43 1 606 68 77-2133 F: +43 1 606 68 77-2139 Room: B.3.14 Favoritenstraße 226 1100 WienPersonal WebspaceLectures 2021/22Engineering> Deep Learning and Virtual Reality Wahlpflichtmodul… Software Design and Engineering moreDeep Learning and Virtual Reality Wahlpflichtmodul MODUL3SWS6ECTS> Master Thesis Project UE Software Design and Engineering moreMaster Thesis Project UELector: DI Dr. techn. Mugdim Bublin, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, DI Jochen Hense, MBA, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Bernhard Taufner, BSc, MSc2SWS6ECTSLecture contentsStudents work individually or in small groups on projects related to software design and software engineering technologies and applications in the context of university R&D activities or within the scope of their individual professional activities. These projects are the practice-relevant basis for the master theses.Assessment methodsContinuous assessment Project progress, proof of function, project presentationLanguageGerman-English> Deep Learning – advanced AI and Data Science ILV Computer Science and Digital Communications moreDeep Learning – advanced AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS6ECTSLecture contents- Deep Learning Foundation- Motivation and basic ideas - Basic principles behind algorithms - Deep Learning Algorithms and Networks- Convolutional Neuronal Networks (CNN) - Recurrent Neural Networks (RNN) - Generative Neural Networks (GAN, Autoencoders) - Reinforcement Learning (Deep QNet) - Applications of Deep Learning and Artificial Intelligence for- Medicine, IoT, Industry 4.0, Autonomous Driving, Games etc.Assessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLanguageEnglish> Deep Learning – advanced AI and Data Science ILV Computer Science and Digital Communications moreDeep Learning – advanced AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS6ECTSLecture contents- Deep Learning Foundation- Motivation and basic ideas - Basic principles behind algorithms - Deep Learning Algorithms and Networks- Convolutional Neuronal Networks (CNN) - Recurrent Neural Networks (RNN) - Generative Neural Networks (GAN, Autoencoders) - Reinforcement Learning (Deep QNet) - Applications of Deep Learning and Artificial Intelligence for- Medicine, IoT, Industry 4.0, Autonomous Driving, Games etc.Assessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLanguageEnglish> Bachelor Thesis 1 SE Computer Science and Digital Communications moreBachelor Thesis 1 SELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc1SWS4ECTSLecture contents- Independent work on a topic from the area of Computer Science, primarily based on the technical topics of the elective modules in the 4th and 5th semesters at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 1Assessment methodsFinal exam Approbation of bachelor thesisTeaching methodsImplementation of a project and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 1 at regular intervals and put it up for discussion.LanguageGerman> Elective Project 2 UE Computer Science and Digital Communications moreElective Project 2 UELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc2SWS5ECTSLecture contentsStudents apply the skills acquired to complete a project in a coordinated and structured manner. project in a coordinated and structured manner. In doing so, they independently define a concrete sub-goal in the project. A well-founded theoretical approach is thus combined with practical application. Collaboration on an industrial R&D project or on current problems within the framework of the R&D activities of the UAS is possible.Assessment methodsFinal exam Practical project in small groups.Teaching methodsGroup work, practical project implementation accompanied with exercises and coaching.LanguageGerman> Bachelor Thesis 1 SE Computer Science and Digital Communications moreBachelor Thesis 1 SELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc, Sebastian Ukleja, BSc1SWS4ECTSLecture contents- Independent work on a topic from the area of Computer Science, primarily based on the technical topics of the elective modules in the 4th and 5th semesters at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 1Assessment methodsFinal exam Approbation of bachelor thesisTeaching methodsImplementation of a project and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 1 at regular intervals and put it up for discussion.LanguageGerman> Elective Project 2 UE Computer Science and Digital Communications moreElective Project 2 UELector: DI Dr. techn. Mugdim Bublin, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc, Sebastian Ukleja, BSc2SWS5ECTSLecture contentsStudents apply the skills acquired to complete a project in a coordinated and structured manner. project in a coordinated and structured manner. In doing so, they independently define a concrete sub-goal in the project. A well-founded theoretical approach is thus combined with practical application. Collaboration on an industrial R&D project or on current problems within the framework of the R&D activities of the UAS is possible.Assessment methodsFinal exam Practical project in small groups.Teaching methodsGroup work, practical project implementation accompanied with exercises and coaching.LanguageGerman
> Deep Learning and Virtual Reality Wahlpflichtmodul… Software Design and Engineering moreDeep Learning and Virtual Reality Wahlpflichtmodul MODUL3SWS6ECTS
> Master Thesis Project UE Software Design and Engineering moreMaster Thesis Project UELector: DI Dr. techn. Mugdim Bublin, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, DI Jochen Hense, MBA, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Bernhard Taufner, BSc, MSc2SWS6ECTSLecture contentsStudents work individually or in small groups on projects related to software design and software engineering technologies and applications in the context of university R&D activities or within the scope of their individual professional activities. These projects are the practice-relevant basis for the master theses.Assessment methodsContinuous assessment Project progress, proof of function, project presentationLanguageGerman-English
> Deep Learning – advanced AI and Data Science ILV Computer Science and Digital Communications moreDeep Learning – advanced AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS6ECTSLecture contents- Deep Learning Foundation- Motivation and basic ideas - Basic principles behind algorithms - Deep Learning Algorithms and Networks- Convolutional Neuronal Networks (CNN) - Recurrent Neural Networks (RNN) - Generative Neural Networks (GAN, Autoencoders) - Reinforcement Learning (Deep QNet) - Applications of Deep Learning and Artificial Intelligence for- Medicine, IoT, Industry 4.0, Autonomous Driving, Games etc.Assessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish
> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLanguageEnglish
> Deep Learning – advanced AI and Data Science ILV Computer Science and Digital Communications moreDeep Learning – advanced AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS6ECTSLecture contents- Deep Learning Foundation- Motivation and basic ideas - Basic principles behind algorithms - Deep Learning Algorithms and Networks- Convolutional Neuronal Networks (CNN) - Recurrent Neural Networks (RNN) - Generative Neural Networks (GAN, Autoencoders) - Reinforcement Learning (Deep QNet) - Applications of Deep Learning and Artificial Intelligence for- Medicine, IoT, Industry 4.0, Autonomous Driving, Games etc.Assessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish
> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLanguageEnglish
> Bachelor Thesis 1 SE Computer Science and Digital Communications moreBachelor Thesis 1 SELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc1SWS4ECTSLecture contents- Independent work on a topic from the area of Computer Science, primarily based on the technical topics of the elective modules in the 4th and 5th semesters at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 1Assessment methodsFinal exam Approbation of bachelor thesisTeaching methodsImplementation of a project and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 1 at regular intervals and put it up for discussion.LanguageGerman
> Elective Project 2 UE Computer Science and Digital Communications moreElective Project 2 UELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. DI Dr. Igor Miladinovic, Mag. Dipl.-Ing. Dr.techn. Wolfgang Radinger-Peer, MBA, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc2SWS5ECTSLecture contentsStudents apply the skills acquired to complete a project in a coordinated and structured manner. project in a coordinated and structured manner. In doing so, they independently define a concrete sub-goal in the project. A well-founded theoretical approach is thus combined with practical application. Collaboration on an industrial R&D project or on current problems within the framework of the R&D activities of the UAS is possible.Assessment methodsFinal exam Practical project in small groups.Teaching methodsGroup work, practical project implementation accompanied with exercises and coaching.LanguageGerman
> Bachelor Thesis 1 SE Computer Science and Digital Communications moreBachelor Thesis 1 SELector: DI Dr. techn. Mugdim Bublin, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc, Sebastian Ukleja, BSc1SWS4ECTSLecture contents- Independent work on a topic from the area of Computer Science, primarily based on the technical topics of the elective modules in the 4th and 5th semesters at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 1Assessment methodsFinal exam Approbation of bachelor thesisTeaching methodsImplementation of a project and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 1 at regular intervals and put it up for discussion.LanguageGerman
> Elective Project 2 UE Computer Science and Digital Communications moreElective Project 2 UELector: DI Dr. techn. Mugdim Bublin, Leon Freudenthaler, BSc MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc, Sebastian Ukleja, BSc2SWS5ECTSLecture contentsStudents apply the skills acquired to complete a project in a coordinated and structured manner. project in a coordinated and structured manner. In doing so, they independently define a concrete sub-goal in the project. A well-founded theoretical approach is thus combined with practical application. Collaboration on an industrial R&D project or on current problems within the framework of the R&D activities of the UAS is possible.Assessment methodsFinal exam Practical project in small groups.Teaching methodsGroup work, practical project implementation accompanied with exercises and coaching.LanguageGerman