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> Introduction to AI and Data Science ILV Computer Science and Digital Communications moreIntroduction to AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS5ECTSLecture contents- Mathematical Basics of AI and Data Science- Linear Algebra - Probability Theory and Statistics - Optimization - Introduction to Artificial Intelligence- Problem Solving and Heuristic Search - Logic and Knowledge Representation - Planning, Learning and Decision Making under Uncertainty - Data Science and Machine Learning Fundamentals- Data Collection, Cleaning, Filtering - Model Building - Model Evaluation - Definition of Machine Learning and classes of Machine Learning Algorithms - Machine Learning Classifiers - Evaluation of Machine Learning AlgorithmsAssessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish> Elective Project 1 UE Computer Science and Digital Communications moreElective Project 1 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. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc1SWS4ECTSLanguageGerman> 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> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLecture contentsVirtual and augmented reality include methods for extending real-world content to provide contextual information through intelligent algorithms. Virtual and Augmented Reality are used in various fields, such as: medicine, industry, education, tourism and computer games. To enable Virtual and Augmented Reality, the methods of Artificial Intelligence and Machine Learning especially Deep Learning play a very important role. Virtual and Augmented Reality are important components of Cyber-Physical Systems, which in turn form the basis for digitalization and Industry 4.0. The course covers in particular the following contents: - Application examples of Virtual and Augmented Reality - Requirements for Augmented Reality and Deep Learning applications - Displays, cameras and other sensors for Virtual and Augmented Reality - Calibration and filtering - Computer vision algorithms for object and scene recognition - Localization, tracking and navigation - Deep Learning algorithms and network architectures, especially CNN and RNN - Use of deep learning algorithms in virtual and augmented reality applicationsAssessment methodsFinal exam Group workTeaching methodsLecture, hands-on exercises, case studies, discussion of current literature, implementation of algorithms and applications.LanguageEnglish> Bachelor Thesis 2 SE Computer Science and Digital Communications moreBachelor Thesis 2 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, Dipl.-Ing. Georg Mansky-Kummert, 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, MSc, Sebastian Ukleja, BSc1SWS6ECTSLecture contents- Independent work on a relevant subject based on the technical topics of the elective modules and possibly the Bachelor thesis 1 at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 2Assessment methodsFinal exam Approval of the bachelor thesisTeaching methodsCarrying out a practical work and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 2 at regular intervals and put it up for discussion.LanguageGerman> Introduction to AI and Data Science ILV Computer Science and Digital Communications moreIntroduction to AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS5ECTSLecture contents- Mathematical Basics of AI and Data Science- Linear Algebra - Probability Theory and Statistics - Optimization - Introduction to Artificial Intelligence- Problem Solving and Heuristic Search - Logic and Knowledge Representation - Planning, Learning and Decision Making under Uncertainty - Data Science and Machine Learning Fundamentals- Data Collection, Cleaning, Filtering - Model Building - Model Evaluation - Definition of Machine Learning and classes of Machine Learning Algorithms - Machine Learning Classifiers - Evaluation of Machine Learning AlgorithmsAssessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish> Elective Project 1 UE Computer Science and Digital Communications moreElective Project 1 UELector: DI Dr. techn. Mugdim Bublin, Tobias Buchberger, BSc MSc, 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, Ines Kramer, BSc MSc, 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, BSc1SWS4ECTSLanguageGerman> 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> 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 2 SE Computer Science and Digital Communications moreBachelor Thesis 2 SELector: 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, BSc1SWS6ECTSLanguageGerman> Software Engineering Project 1 UE Software Design and Engineering moreSoftware Engineering Project 1 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, Dipl.-Ing. Georg Mansky-Kummert, 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, MSc1SWS5ECTSLecture contentsSoftware Engineering Project 1 enables students to implement the knowledge acquired during their studies in a concrete project. In the first semester, a concrete problem is analyzed and a design for the software solution is worked out using Advanced Project Management methods. This solution will then be implemented in the software project in the second semester. The LV covers in particular the following contents: - Application of modern project management methods to a concrete project Formulation - , classification and prioritization of requirements for a concrete problem Use of - UML diagrams (Use Case, class, activity and sequence diagrams) for software design design to meet requirements Structured - and standardized documentation of results as a high-level design document that serves as a basis for implementation .Assessment methodsModule examTeaching methodsGroup work, practical project implementation accompanied by exercises and coachingLanguageGerman> Software Engineering Project 2 UE Software Design and Engineering moreSoftware Engineering 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, Dipl.-Ing. Georg Mansky-Kummert, FH-Prof. DI Dr. Igor Miladinovic, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Bernhard Taufner, BSc, MSc1SWS5ECTSLecture contentsSoftware Engineering Project 2 enables students to implement the knowledge acquired during their studies in a concrete project. In the second semester, based on requirements and design draft from the software design project, the software solution is implemented in the first semester using modern software development methods and tools. This implemented solution is then systematically tested and improvements are incorporated. The LV covers in particular the following contents: - Implementation of classes and data structures based on the High Level Design documentUse of - software algorithms for the implementation of activity and sequence diagramsDefinition - and prioritization of test cases under consideration of requirementsConduction of - test scenarios with current test toolsAssessment methodsModule examTeaching methodsGroup work, practical project implementation accompanied by exercises and coachingLanguageGerman> 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 presentationTeaching methods-LanguageGerman-English> Deep Learning and Virtual Reality Wahlpflichtmodul… Software Design and Engineering moreDeep Learning and Virtual Reality Wahlpflichtmodul MODUL3SWS6ECTS> Master Thesis Seminar SE Software Design and Engineering moreMaster Thesis Seminar SELector: 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. 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, MSc2SWS4ECTSLecture contents- Deepening the basic principles of scientific work - Reading, understanding and interpreting relevant scientific texts - Literature research - Formal methods of scientific work - Students present the current development of their Master's thesis at regular intervals and put it up for discussion in the plenumAssessment methodsContinuous assessment Presentations, home exercisesTeaching methodsLecture, Case StudiesLanguageGermanPublications The publications of Mugdim Bublin written at FH Campus Wien can be found in our publication database, others in the personal web space.
> Introduction to AI and Data Science ILV Computer Science and Digital Communications moreIntroduction to AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS5ECTSLecture contents- Mathematical Basics of AI and Data Science- Linear Algebra - Probability Theory and Statistics - Optimization - Introduction to Artificial Intelligence- Problem Solving and Heuristic Search - Logic and Knowledge Representation - Planning, Learning and Decision Making under Uncertainty - Data Science and Machine Learning Fundamentals- Data Collection, Cleaning, Filtering - Model Building - Model Evaluation - Definition of Machine Learning and classes of Machine Learning Algorithms - Machine Learning Classifiers - Evaluation of Machine Learning AlgorithmsAssessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish
> Elective Project 1 UE Computer Science and Digital Communications moreElective Project 1 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. Dipl.-Ing. Heimo Hirner, FH-Prof. DI Dr. Igor Miladinovic, Silvia Schmidt, BSc MSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc1SWS4ECTSLanguageGerman
> 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
> Virtual and Augmented Reality ILV Computer Science and Digital Communications moreVirtual and Augmented Reality ILVLector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer3SWS6ECTSLecture contentsVirtual and augmented reality include methods for extending real-world content to provide contextual information through intelligent algorithms. Virtual and Augmented Reality are used in various fields, such as: medicine, industry, education, tourism and computer games. To enable Virtual and Augmented Reality, the methods of Artificial Intelligence and Machine Learning especially Deep Learning play a very important role. Virtual and Augmented Reality are important components of Cyber-Physical Systems, which in turn form the basis for digitalization and Industry 4.0. The course covers in particular the following contents: - Application examples of Virtual and Augmented Reality - Requirements for Augmented Reality and Deep Learning applications - Displays, cameras and other sensors for Virtual and Augmented Reality - Calibration and filtering - Computer vision algorithms for object and scene recognition - Localization, tracking and navigation - Deep Learning algorithms and network architectures, especially CNN and RNN - Use of deep learning algorithms in virtual and augmented reality applicationsAssessment methodsFinal exam Group workTeaching methodsLecture, hands-on exercises, case studies, discussion of current literature, implementation of algorithms and applications.LanguageEnglish
> Bachelor Thesis 2 SE Computer Science and Digital Communications moreBachelor Thesis 2 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, Dipl.-Ing. Georg Mansky-Kummert, 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, MSc, Sebastian Ukleja, BSc1SWS6ECTSLecture contents- Independent work on a relevant subject based on the technical topics of the elective modules and possibly the Bachelor thesis 1 at a scientific level under the guidance of a supervisor. - Elaboration of the bachelor thesis 2Assessment methodsFinal exam Approval of the bachelor thesisTeaching methodsCarrying out a practical work and elaboration as a bachelor thesis with coaching. Students present the current development of their bachelor thesis 2 at regular intervals and put it up for discussion.LanguageGerman
> Introduction to AI and Data Science ILV Computer Science and Digital Communications moreIntroduction to AI and Data Science ILVLector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder3SWS5ECTSLecture contents- Mathematical Basics of AI and Data Science- Linear Algebra - Probability Theory and Statistics - Optimization - Introduction to Artificial Intelligence- Problem Solving and Heuristic Search - Logic and Knowledge Representation - Planning, Learning and Decision Making under Uncertainty - Data Science and Machine Learning Fundamentals- Data Collection, Cleaning, Filtering - Model Building - Model Evaluation - Definition of Machine Learning and classes of Machine Learning Algorithms - Machine Learning Classifiers - Evaluation of Machine Learning AlgorithmsAssessment methodsContinuous assessment - Project work - Exercises during lectures - Final written examTeaching methods- Lecture - Group work (project) - Practical exercises - Continuous Discussion and feedbackLanguageEnglish
> Elective Project 1 UE Computer Science and Digital Communications moreElective Project 1 UELector: DI Dr. techn. Mugdim Bublin, Tobias Buchberger, BSc MSc, 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, Ines Kramer, BSc MSc, 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, BSc1SWS4ECTSLanguageGerman
> 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
> 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 2 SE Computer Science and Digital Communications moreBachelor Thesis 2 SELector: 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, BSc1SWS6ECTSLanguageGerman
> Software Engineering Project 1 UE Software Design and Engineering moreSoftware Engineering Project 1 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, Dipl.-Ing. Georg Mansky-Kummert, 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, MSc1SWS5ECTSLecture contentsSoftware Engineering Project 1 enables students to implement the knowledge acquired during their studies in a concrete project. In the first semester, a concrete problem is analyzed and a design for the software solution is worked out using Advanced Project Management methods. This solution will then be implemented in the software project in the second semester. The LV covers in particular the following contents: - Application of modern project management methods to a concrete project Formulation - , classification and prioritization of requirements for a concrete problem Use of - UML diagrams (Use Case, class, activity and sequence diagrams) for software design design to meet requirements Structured - and standardized documentation of results as a high-level design document that serves as a basis for implementation .Assessment methodsModule examTeaching methodsGroup work, practical project implementation accompanied by exercises and coachingLanguageGerman
> Software Engineering Project 2 UE Software Design and Engineering moreSoftware Engineering 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, Dipl.-Ing. Georg Mansky-Kummert, FH-Prof. DI Dr. Igor Miladinovic, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Bernhard Taufner, BSc, MSc1SWS5ECTSLecture contentsSoftware Engineering Project 2 enables students to implement the knowledge acquired during their studies in a concrete project. In the second semester, based on requirements and design draft from the software design project, the software solution is implemented in the first semester using modern software development methods and tools. This implemented solution is then systematically tested and improvements are incorporated. The LV covers in particular the following contents: - Implementation of classes and data structures based on the High Level Design documentUse of - software algorithms for the implementation of activity and sequence diagramsDefinition - and prioritization of test cases under consideration of requirementsConduction of - test scenarios with current test toolsAssessment methodsModule examTeaching methodsGroup work, practical project implementation accompanied by exercises and coachingLanguageGerman
> 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 presentationTeaching methods-LanguageGerman-English
> Deep Learning and Virtual Reality Wahlpflichtmodul… Software Design and Engineering moreDeep Learning and Virtual Reality Wahlpflichtmodul MODUL3SWS6ECTS
> Master Thesis Seminar SE Software Design and Engineering moreMaster Thesis Seminar SELector: 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. 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, MSc2SWS4ECTSLecture contents- Deepening the basic principles of scientific work - Reading, understanding and interpreting relevant scientific texts - Literature research - Formal methods of scientific work - Students present the current development of their Master's thesis at regular intervals and put it up for discussion in the plenumAssessment methodsContinuous assessment Presentations, home exercisesTeaching methodsLecture, Case StudiesLanguageGerman