Details

René Goldschmid, MSc

Academic Staff

rene.goldschmid@fh-campuswien.ac.at
+43 1 606 68 77-2146
+43 1 606 68 77-2139

Room: C.1.08b
Favoritenstraße 226
1100 Wien


Lectures 2022/23

Engineering

Introduction to AI and Data Science ILV
Computer Science and Digital Communications more

Introduction to AI and Data Science ILV

Lector: DI Dr. techn. Mugdim Bublin, René Goldschmid, MSc, Matthias Schmid-Kietreiber, Dr. Christian Steineder

3 SWS   5 ECTS

Lecture 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 Algorithms

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

Software Engineering ILV
Computer Science and Digital Communications more

Software Engineering ILV

Lector: Mag. Dipl.-Ing. Peter Gerstbach, René Goldschmid, MSc, Dipl.-Ing. Georg Mansky-Kummert, FH-Prof. DI Dr. Igor Miladinovic

4 SWS   7 ECTS

Lecture contents

This lecture aims to explain the technical, organizational and economic aspects of software engineering. Organizational possibilities for structuring software development in the form of process models, such as waterfall model, spiral model and agile models are presented. The technical aspects of software engineering focus on the creation of object-oriented systems and their modeling.
The course covers in particular the following contents:
- Software Engineering Activities,
- Requirements Engineering,
- use cases,
- high-level design
- UML activity diagrams,
- UML class diagrams,
- UML sequence diagrams,
- Software testing,
- software process models and
- Agile software development.

Assessment methods

Final exam

Individual and group works

Teaching methods

Blended learning, guest lectures, experiental learning, coaching

Language

German

Bachelor Thesis 1 SE
Computer Science and Digital Communications more

Bachelor Thesis 1 SE

Lector: DI Dr. techn. Mugdim Bublin, Tobias Buchberger, BSc MSc, FH-Prof. DI Thomas Fischer, Leon Freudenthaler, BSc MSc, René Goldschmid, MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. Dipl.-Ing. Manuel Koschuch, Bakk. tech., Ines Kramer, BSc MSc, Dipl.-Ing. Georg Mansky-Kummert, FH-Prof. DI Dr. Igor Miladinovic, Silvia Schmidt, BSc MSc, Bernhard Taufner, BSc, MSc

1 SWS   4 ECTS

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

Introduction to AI and Data Science ILV
Computer Science and Digital Communications more

Introduction to AI and Data Science ILV

Lector: DI Dr. techn. Mugdim Bublin, René Goldschmid, MSc, Matthias Schmid-Kietreiber, Dr. Christian Steineder

3 SWS   5 ECTS

Lecture 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 Algorithms

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

Software Engineering ILV
Computer Science and Digital Communications more

Software Engineering ILV

Lector: Mag. Dipl.-Ing. Peter Gerstbach, René Goldschmid, MSc, Dipl.-Ing. Georg Mansky-Kummert, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc

4 SWS   7 ECTS

Lecture contents

This lecture aims to explain the technical, organizational and economic aspects of software engineering. Organizational possibilities for structuring software development in the form of process models, such as waterfall model, spiral model and agile models are presented. The technical aspects of software engineering focus on the creation of object-oriented systems and their modeling.
The course covers in particular the following contents:
- Software Engineering Activities,
- Requirements Engineering,
- use cases,
- high-level design
- UML activity diagrams,
- UML class diagrams,
- UML sequence diagrams,
- Software testing,
- software process models and
- Agile software development.

Assessment methods

Final exam
Individual and group works

Teaching methods

Blended learning, guest lectures, experiental learning, coaching

Language

German

Bachelor Thesis 1 SE
Computer Science and Digital Communications more

Bachelor Thesis 1 SE

Lector: DI Dr. techn. Mugdim Bublin, Tobias Buchberger, BSc MSc, Leon Freudenthaler, BSc MSc, René Goldschmid, MSc, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka, FH-Prof. Dipl.-Ing. Heimo Hirner, FH-Prof. Dipl.-Ing. Manuel Koschuch, Bakk. tech., Ines Kramer, BSc MSc, FH-Prof.in Mag.a Dr.in Sigrid Schefer-Wenzl, MSc BSc, Dr. Christian Steineder, Bernhard Taufner, BSc, MSc, Sebastian Ukleja, BSc

1 SWS   4 ECTS

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, René Goldschmid, 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, BSc

2 SWS   5 ECTS

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

Advanced Software Development ILV
Software Design and Engineering more

Advanced Software Development ILV

Lector: René Goldschmid, MSc

3 SWS   5 ECTS

Lecture contents

Software is subject to an ageing process that can be assessed by key figures. In the course of the Advanced Software Development course, concepts are taught on how code quality can be assessed. On the basis of key figures methods are shown with the help of tools to improve the code quality. These measures can only be implemented meaningfully with the help of configuration management.
The LV covers in particular the following contents:
- Configuration Management (SVN/git)
- Setting up a project in Configuration ManagementBasic
- concepts when working with a configuration management toolOverview of
- Software Design PatternsRefactoring
- , Bad SmellsCode
- QualitySoftware
- Key Figures

Assessment methods

Final exam
Group work

Teaching methods

Lecture with slides, hands on training on a software project in the group.

Language

German