Details

DI Dr. techn. Mugdim Bublin

Academic Staff
Stadt Wien Endowed Professorship for Artificial Intelligence


T: +43 1 606 68 77-2133
F: +43 1 606 68 77-2139

Room: B.3.14
Favoritenstraße 226
1100 Wien

Personal Webspace


Lectures 2021/22

Engineering

> Deep Learning and Virtual Reality Wahlpflichtmodul…
Software Design and Engineering more

Deep Learning and Virtual Reality Wahlpflichtmodul MODUL

3SWS
6ECTS
> Master Thesis Project UE
Software Design and Engineering more

Master Thesis Project UE

Lector: 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, MSc

2SWS
6ECTS

Lecture contents

Students 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 methods

Continuous assessment
Project progress, proof of function, project presentation

Language

German-English

> Deep Learning – advanced AI and Data Science ILV
Computer Science and Digital Communications more

Deep Learning – advanced AI and Data Science ILV

Lector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder

3SWS
6ECTS

Lecture 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 methods

Continuous assessment
- Project work
- Exercises during lectures
- Final written exam

Teaching methods

- Lecture
- Group work (project)
- Practical exercises
- Continuous Discussion and feedback

Language

English

> Virtual and Augmented Reality ILV
Computer Science and Digital Communications more

Virtual and Augmented Reality ILV

Lector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer

3SWS
6ECTS

Language

English

> Deep Learning – advanced AI and Data Science ILV
Computer Science and Digital Communications more

Deep Learning – advanced AI and Data Science ILV

Lector: DI Dr. techn. Mugdim Bublin, Dr. Christian Steineder

3SWS
6ECTS

Lecture 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 methods

Continuous assessment
- Project work
- Exercises during lectures
- Final written exam

Teaching methods

- Lecture
- Group work (project)
- Practical exercises
- Continuous Discussion and feedback

Language

English

> Virtual and Augmented Reality ILV
Computer Science and Digital Communications more

Virtual and Augmented Reality ILV

Lector: DI Dr. techn. Mugdim Bublin, Mag. art Philipp Lammer

3SWS
6ECTS

Language

English

> Bachelor Thesis 1 SE
Computer Science and Digital Communications more

Bachelor Thesis 1 SE

Lector: 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, MSc

1SWS
4ECTS

Lecture 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 1

Assessment methods

Final exam
Approbation of bachelor thesis

Teaching methods

Implementation 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.

Language

German

> Elective Project 2 UE
Computer Science and Digital Communications more

Elective Project 2 UE

Lector: 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, MSc

2SWS
5ECTS

Lecture contents

Students 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 methods

Final exam
Practical project in small groups.

Teaching methods

Group work, practical project implementation accompanied with exercises and coaching.

Language

German

> Bachelor Thesis 1 SE
Computer Science and Digital Communications more

Bachelor Thesis 1 SE

Lector: 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, BSc

1SWS
4ECTS

Lecture 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 1

Assessment methods

Final exam
Approbation of bachelor thesis

Teaching methods

Implementation 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.

Language

German

> Elective Project 2 UE
Computer Science and Digital Communications more

Elective Project 2 UE

Lector: 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, BSc

2SWS
5ECTS

Lecture contents

Students 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 methods

Final exam
Practical project in small groups.

Teaching methods

Group work, practical project implementation accompanied with exercises and coaching.

Language

German