ERASMUS and International Incoming Students

Courses available in English for Exchange Students of the Degree Programme Information Technology and Systems Management

Incoming exchange students are basically flexible in their selection of courses (units). You can choose from all levels as long as it is guaranteed that you fulfil the prerequisites for the selected course.

In case of doubt, please contact the International Coordinator of the programme. You can also choose from the courses listed below from the Master programme Applied Image and Signal processing.

Please note that courses are offered only either in the winter (= end of September to end of January) or the summer semester (= end of February to June).

Master Programme Information Technology and Systems Management

Semester 1 (Winter Semester)

Digital Signal Processing 1 (4 ECTS Credits)
Theory of discrete signals and systems: discrete Fourier transformation (FFT), power density spectrum, discrete convolution and correlation, interpolation, implementation in Matlab and C; z-transform, z transfer function, stability and frequency response of discrete systems, discretisation of continuous systems (bilinear transformation, impulse invariant transformation)Digital filters: principle and design of FIR filters, simulation with simulation tools (e.g. Matlab), principle and designof IIR filters, filter implementation in Matlab and C.

Selected Topics in Mathematics and Modelling (3 ECTS Credits)
Selected chapters from analysis (multidimensional differentiation and integration), algebra (vector spaces with inner product, eigenvalue theory, orthonormal bases, coordinate transformation, examples of vector spaces and applications), numerics (error analysis, conditioning and algorithmics) and Matlab (CLI and programming).

Advanced Presentation Skills  (2 ECTS Credits)
On course completion, students are  able to demonstrate that they  can

  • identify relevant success factors for effective presentations in English
  • apply adequate phrases for opening and closing a presentation as well as for signposting and overcoming difficulties
  • analyse and assess a presentation according to a set of defined criteria
  • use the storyboard method for designing a 5 minute presentation tailored to a specific target group
  • justify the selection and structuring of the materials used in that presentation
  • formulate appropriate questions with respect to a presentation
  • provide well-structured and clear answers during the Q&A session following a presentation


Semester 2 (Summer Semester)

Applied Statistics (3 ECTS Credits)
Estimation theory: point and interval estimators, confidence intervals; application to stochastic simulations: random number generators, simulation model, result analysis; statistical test theory: comparison of mean values, significance, outlook ANOVA; application within data mining: pre-processing, feature extraction, outlook: PCA

Digital Signal Processing 2 (4 ECTS Credits)
filter structures, 2nd order section IIR filters, frequency transformations, special filters (notch filter, comb filter), implementation in Matlab and C principle and theory of adaptive FIR filters (LMS-filter); basics of digital controlling, simple digital controller (design and implementation); transmission of digital signals, 2D signal processing basics.

Discussion and Argumentation Skills (2 ECTS Credits)
On course completion, students are able to demonstrate that they can

  • identify relevant success factors for compelling argumentation
  • define and apply argumentation strategies for an identified purpose
  • demonstrate the usage of adequate phrases and rhetorical strategies in discussions / meetings / negotiations
  • anticipate somebody’s interests / arguments and apply context-relevant strategies to constructively address these for the defined purpose
  • analyse and assess somebody’s strengths and weaknesses in discussions and their preparation  according to a set of defined criteria
  • apply the Harvard Method for the preparation of a specific debate and in negotiations


Semester 3 (Winter Semester)

Data Mining (2.5 ECTS Credits)
Special applications or topics related to knowledge discovery and big data: Introduction and overview of big data applications, related issues and methods; MapReduce; Merging of data sets; Analysis of text data: natural language pro- cessing, tokenization, Boolean information retrieval, term vocabulary and postings lists, phrase queries, wildcard queries, spelling correction, tolerant retrieval, ranking of search results using the vector space model; Outlook: special topics not covered so far; Analysis of graphs or links: e.g. PageRank; Analysis of distances or similarities, Finding of representative examples: spectral clustering, affinity propagation; Analysis of data sets with mixed data types: e.g. decision trees, graphical models; Visualization and dimension reduction using SOMs, LLE, Isomap, growing neural gas algorithm; Special applications: Frequent itemset mining and association rules, finding similar data, recommender services.

Pattern Recognition 1 (2.5 ECTS Credits)
Pattern recognition process (data preprocessing, feature extraction, feature reduction, classification); preprocessing and dimension reduction (PCA, Z-score, atan); training, validation and testing data (sampling, crossvalidation); Baysian decision theory; mathematical models for the likelihood; types of error and performance analysis (true/false positives and negatives; risk vs. error; spec and sens, ROC); Overview on other methods and algorithms: SVMs, HMMs, NNs; Clustering: hierarchical clustering, partitioning clustering, k-means.

Innovation Management (3 ECTS Credits)
Structure of the innovation process and its key indicators, assessment and prioritization of ideas, further methods such as business model generation, Lean Canvas and Blue Ocean strategies to deepen the ideas of a traditional business plan. Trends such as open innovation, conditions for successful innovation, lean start-up process / "traditional" product development - advantages and disadvantages.

Ethics and Sustainability (1 ECTS Credits)
Introduction to issues related to business ethics and sustainability, in particular with the theoretical relationship between business, economics and ethics. The importance of ethical behaviour for the daily business and its impact for the “environment” (e.g. stakeholder) is another priority. Practical case studies are connected with relationships in strategic management. In the discussion of new trends and the resulting challenges for the entrepreneur (for example in the context of "Corporate Social Responsibility") special considerations are given.

Intercultural Communication Skills (1 ECTS Credit)
On completion of the course participants are able to

  • recognize the impact of cultural factors on perception and interaction with others
  • assess the relevance of their own cultural value system and culturally influenced world view
  • apply the DICE model as a means to increase intercultural competence especially with respect to suspension of judgement and perspective shifting

Aspects covered in the practice sessions include team-building across cultures, communication styles including non-verbal communication, perspective shifting as well as stereotyping versus cultural generalization

 

ELECTIVES IN THE SPECIALIZATION AREAS

Adaptive Software Systems (6 ECTS Credits)
Adaptive object models and their application; Application integration; vendor-independent generic software platforms; Mobile services and cloud applications; Architectures for migrating applications or software agents; Simulation and test of mobile and migrating applications; Selected topics for software specialists.

Robot Kinematics (6 ECTS Credits)
Kinematic configurations and components of industrial robots, spatial transformations, DH-Convention, Forward and Backward Kinematics, velocities and static forces at the end effector, Jacobi Matrix, Singularities, Differential Backward Kinematics, Basics of the Newton-Euler Dynamics, practical introduction into robot programming, kinematic simulation in MATLAB.

Medical Imaging and Image Processing (6 ECTS Credits)
Medical imaging (x-ray, CT, MRI,…) and corresponding methods and algorithms for image processing (image enhancement, low-level processing, segmentation, registration, classification); review of software tools and libraries; generation of 3D surface models (marching cubes), graphical rendering and photo-realistic image synthesis.

Protocol Design and Validation (6 ECTS Credits)
Processes and threads, synchronization of processes and threads, inter-process communication, shared memory, concurrent program, distributed program, concurrent programming, concurrent programming abstraction, consensus; Parallel computing, classification of parallel architectures; Levels of parallelism; Techniques of functional and data decomposition; Parallel systems / hardware; Selected topics in concurrent and parallel computing.

Modelling, Simulation and Optimization (6 ECTS Credits)
Application of simulation models in the field of demand-response and real-time control. Special focus is given to communication technology models that influence the transient behaviour of energy generation and distribution, integrated simulation tools (co-simulation) for the integration of decentralised energy providers in IP-based communication networks. Demand-response models / optimization through simulation; cascading effects in relation to risks in ICT and energy systems

Business Leadership (3 ECTS Credits)
Introduction to corporate governance and management, leadership theories, leadership styles, management functions / tasks management process / systems target systems, planning, decision-making, organizing, leading, controlling, management processes - application with examples of corporate development; Discourse regarding leadership models (transactiononal, transformal), leadership theory, fundamentals of leadership, differentiation Leadership and Management, Leadership levels, leadership on team and organizational level, strategic leadership. Outcome assessment, application of performance measurement systems; realization and chances of success, change management, business development, lean management, human resource management, time management, coordination and conflict management, modern management approaches, foundation management, virtual business, developing a business idea, development of a business plan, implementation of innovative simulation games ("Apollo 13," "target SIM" ).

ERP Systems (3 ECTS Credits)
Integration and practical implementation of  Enterprise Resource Planning (ERP) into company's existing resources (capital value, equipment or personnel);  most efficient way for daily operations and optimization of the management of business processes. The discussion will differentiate between the technical orientation (target sector), the scalability and the different company sizes (number of required users or company locations). Also the range of functions, the upcoming technologies (databases, programming languages, layered architectures, operating systems) are supported in the practical implementation with a structured approach to a real ERP system; a certification is offered as an option.

Parallel Computing - Parallel Computing (3 ECTS Credits)
Processes and threads, synchronization of processes and threads, inter-process communication, shared memory, concurrent program, distributed program, concurrent programming, concurrent programming abstraction, consensus; Parallel computing, classification of parallel architectures; Levels of parallelism; Techniques of functional and data decomposition; Parallel systems / hardware; Selected topics in concurrent and parallel computing.

Image Processing (3 ECTS Credits)
Human and computer vision, image acquisition (CCD, CMOS, IR,…), image enhancement (gray-level transformation, histogram equalization, spatial filtering, Laplace method, frequency filtering, Wiener filter, bandpass and notch filters); processing of color images; morphological operators (dilation, erosion, closing, opening, hit-or-miss, thinning, thicking, skeletons, convex hull); segmentation (thresholding, adaptive thresholding, canny-edge, Hough-tranformation, region grow, watershed, Gauss- and Laplace pyramid, active contours); features (shape, Fourrier and statistical descriptors, Harris detector, SIFT, MSER, SURF,…); object recognition and object matching (min.-distance, correlation analysis, Bayes classification).

Big Data Engineering (3 ECTS Credits)
Paradigms and characteristics of big data computing; Architectural models for data-intensive applications; Overview of common big data frameworks; Concept overview of crowdsourcing, data fusion and data integration; Cloud-based infrastructures for data-intensive software development; Real-time delivery of results from big data analytics; Programming techniques for data-intensive applications, implementation of case studies; Selected topics in big data computing.

 

Master Programme Applied Image Signal Processing

First Semester (Winter semester)

Digital Signal Processing 1 (Project – 2 ECTS Credits)
Solution of project based exercises related to the content of the lecture Digital Signal Processing 1 (see description of course above).

Signals and Systems 1 (2 ECTS Credits)
Basic signal and system properties, time and frequency domain, Fourier series and Fourier transformation (FT), FT of single impulses and periodic signals, power density spectrum (Parseval), convolution, convolution property, dirac impulse, dirac impulse sequence, stochastic signals, variance and power of stochastic signals, autocorrelation and cross correlation sampling theorem, aliasing, zero order hold sampling, quantisation, quantisation error, Laplace transformation, transfer function, pole zero map, discrete time signals and systems, z-transform, z-transfer function.

Hardware Oriented Signal Processing 1 ( 1.5 ECTS Credits)
Signal acquisition, sensors, signal amplifiers, digital-analog-converters (DACs), types of DACs, analog-digital converters (ADCs), ADC-types and architectures, measurement devices and –systems, measurement and analysis of signal properties.

Semester 2 (Summer Semester)

Digital Signal Processing 2 (Project – 2 ECTS Credits)
Solution of project based exercises related to the content of the lecture Digital Signal Processing 2 (see description of course above).

Signals and Systems 2 (2 ECTS Credits)
stability examination of continuous and discrete systems (root locus),
analog standard filters (Butterworth, Tschebyscheff, Cauer, Bessel), principle of controlling, control loop, design of simple controllers, pid controller, fuzzy logic.

Semester 3 (Winter Semester)

IT-Project Management and Software Projects (3.5 ECTS Credits)
Planning of product innovation: project definition, task structure, quality assurance, work packages, organisation, roles, phases, milestones/results, flow chart, multi-project control; implementation and controlling: conflict line/project, progress monitoring, prognosis, risk analysis, reporting system, qualitative and quantitative evaluation, documentation, software models and tools; social skills: teamwork, challenge, expectation, self-organisation, moderation, feedback, management styles, roles within a team, coaching of projects.


The following two courses are offered alternatively every year. Please make sure that you have verified that the selected course is offered in the semester you want to come to Salzburg!


Selected Topics in Hardware Oriented Signal Processing (5 ECTS Credits) – Winter Semester 2015/16

Functional principle of modern signal processors, fixed point formats, special hardware architectures (FPGAs), modern development environments and simulation tools, speed optimization of signal processing algorithms, parallelisation in software and hardware, hardware description languages (VHDL).

Literature: Chassaing, R. & Reay, D. (2008) Digital Signal Processing and Applications with the TMS 320C6713 and TMS 320C6416 DSK. John Wiley & Sons, New Jersey.

Medical Imaging (5 ECTS Credits)
On completion of the course students are able to understand basics of different medical imaging modalities and their application in a clinical environment. Furthermore knowledge on basic anatomy and image representation as well as on methods dealing with advanced segmentation and registration of 4d data and 3D model rendering is given in a medical context. Students will also be able to apply their knowledge gained from prior courses onto medical images for the purpose of analysis, visualisation and diagnostics.

Literature: Dougherty, G. (2009) Digital Image Processing for Medical Applications. Cambridge University Press, Cambridge.; Smith, N. B. (2010) Introduction to Medical Imaging: Physics, Engineering and Clinical Applications. Cambridge; University Press, Cambridge.; Deserno, T. M. (2011) Biomedical Image Processing. Springer, Berlin.; Birkfellner, W. (2011) Applied Medical Image Processing. CRC Press, London.

See also courses offered in the Bachelor Information Technology & Systems-Management


As an accepted incoming student you can also choose among the Courses offered by the International Office.

For administrative issues, please, contact the Incoming Students Coordinator at International Office, Teresa Rieger (teresa.riegerfh-salzburg.ac.at).

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