Emotional expressions are important signals for people to make sense of situations, actions and relationships in their social interactions with each other. Is the empowerment of technological systrms with the capacity to also sense and express emotions able to improve their users’ interactions with them? This question is the driving force behind the field of Affective Computing.

The students know different theories of emotions, contrast them with each other and debate them. They apply the acquired knowledge by addressing problems from within the primary areas of application for Affective Computing through the development of  prototypical interactive systems that are capable of sensing or expressing emotions.

The lecture teaches the construction of mobile media applications. The main concepts are discussed using the Android platform. In a first partt, the basic technologies and limitations of mobile devices are shown. The second part examins different development strategies like native applications, device independend abstractions and web applications. A main part of the lecture is the integration of different media types into mobile applications and the constraints the developer has to keep in mind.

Leacture with exercise

The lecture Big Data Engineering addresses the systematic construction of data-intensive systems. Generic architectural approaches are introduced in order to design robust, performant and scalable data systems for various applications. For different architectural areas various kinds of data storage and processing models are discussed. Topics include, among others, distributed file systems, serialization, batch and stream processing with MapReduce and other programming models, queuing mechanisms and NoSQL databases. These are both conceptually described as well as implemented by means of exemplary tools and techniques. The focus is on established industry standards such as Apache Thrift, Hadoop, Kafka, Cassandra, Storm. These are illustrated by means of an exemplary Web Analytics application.

During the course students acquire, among others, the following abilities:

• They evaluate different approaches of data systems for given application problems with specific requirements.
• They describe structure and function of specific architectural approaches for Big Data systems.
• They categorize tools and techniques for Big Data systems and utilize them professionally.
• They design architecture and data models as well as processing logic and queries for given Big Data applications and implement these based on specific open source tools and techniques.

Independent work relates to the preparation and followup of lectures, laboratory exercises and exam preparation.

• Introduction and business-management background
• The concept of data warehousing
• Business Analytics and Balanced Scorecard (BSC)
• CRM and Data Mining
• Trends in Business Intelligence-Case studies

• Defining a business process and types of business processes
• Analyzing business processes
• Modelling business processes
• Tools for modelling business processes
• Simulating business processes with ARENA
• Enterprise SOA: SAP’s vision of a service-oriented-architecture
• KPI’s for the evaluation of business processes

The buzzword "Cloud" represents a variety of interesting technologies which gained importance in the life of a computer science professional. Those are being collected, examined, explained and understood during the course. Primary objective is usefulness for the student, regardless of whether he acts as a cloud user, developer, administrator or even entrepreneur. Understand the broad meaning of "Cloud Computing" from a variety of perspectives: Definition, use cases, technology basics, key players, APIs, scaling, redundancy …

Enterprise analysis, software choice, system integration, basics of customizing, small development task in ABAP in addition to an ABAP introduction, optional: project office: integrated project and service processing with SAP ECC 6.0

Lecture, workshops, lab:

Case study based participation in group oriented workshops about enterprise analysis, presentation of group results, independent implementation of the analysis results of into SAP by appropriate system customizing in the lab. Independent treatment of another lab task (e.g., ABAP course, case study project office)

The lecture first deals with SWT/JFace and the Eclipse Rich Client Platform 4 (RCP), which uses SWT and JFace as its basis. The most important topics are the model-view-controller pattern, layout management and event handling using the observer pattern. Based upon this techniques advanced technologies like the separation of business logic and user interface code using data binding and dialog control are presented. Other topics are internationalization and multithreading in the context of user interfaces. The last part of the lecture shows the declarative construction of user interfaces and the application of the RCP framework.

Lecture preparation, exam preparation, implementing the bonus exercise, 30% of the lecture is held as a computer exercise

Consulting market, basic methods and analysis tools, peculiarities of IT consulting, basis types of case studies.

Participation lecture, development of an interactive role play in the group, individual execution of a short case study.

Technological and topological mechanisms for securingnetworks, attack patterns and defense mechanisms againstthem. Basics of, variants of and defense against malicioussoftware. Analysis and judgement of security mechanismsand related activities. Excercies at the end of each semester provide practicalexperience in dealing with security topics.

Presentation with a lot of room for discussions andinteraction. Finalized by a hands-on session.

This course covers principles and tools for the compilation and analysis of programs.

Selection of topics covered:

• Syntax analysis (Parser Tools/Generators)
• Semantics of programs
  • Typesystems
  • Operational semantics
  • Interpreters/Virtual machines
• Program analysis

Prerequisistes

• Some programming experiences
• Logic (propositional logic)

Mix of lecture and exercis. In case of an oral examination, group work will be permitted.

This course introduces the principles, theories and concepts of statistics and data modelling.

Students will learn

• how to construct and interpret graphical presentations of data,
• conduct appropriate statistical tests, use the appropriate techniques in data modelling,
• interpret the results generated,
• apply these statistics and data modelling techniques in practical projects, and
• develop real world analytics solutions using Spark Machine Learning and Scala.

Prerequisites:

Target audience are 6th and 7th semester students. If in doubt contact lecture in charge.

Assessment:

• Continuous assessment (individual)
• Group project (presentation + term paper)

Intensive course, given within the first two weeks of October. Schedule TBA.

Teaching staff: Dr. Kenny Lu, Dr. Noi Sian Koh (Nanyang Polytechnic Singapore)

Risk minimisation

Baysian decision theory

Decision functions

Perceptrons

Linear machines

Multi-Layer-Perceptrons

k-Nearest-Neighbor classifiers

Support vector machines

Feature assessment via distance and separability measures

Principal component analysis

Class (including training) 50%, self-responsible work 50%

The course offers an introduction to the methods and techniques used in Boolean Satisfiability (SAT) solving and Aautomated Planning. The students will learn how to use SAT solvers and automated planners and also how they work. The topics covered in the lecture include:

• Practical applications of SAT solving
• The DPLL/CDCL algorithm and how they are implemented
• Local search SAT solving algorithms
• Encoding problems as SAT problems and selecting the proper SAT solver
• Applications of automated planning
• Formalization of planning problems and the PDDL language
• Basic state space search algorithms (forwards/backwards search)
• Heuristic search algorithms and planning heuristics
• Satisfiability based planning
• Hierarchical task network planning
• classical scheduling approaches
• constraint-based scheduling
• planning for virtual agents in computer games

Ziele:

• The students will be able to model various problems as SAT or as planning tasks in the PDDL language and solve them using off-the-shelf solvers.
• The students will understand the approaches used in SAT solving and automated planning algorithms, which will allow them to efficiently model and solve real world problems by selecting the proper tools for the given task.

TERP10: SAP ERP - Integration of Business Processes is a 10-day training course held at the universities participating in the pilot project. The students learn how the fundamental integrative business processes in procurement, production, planning, project management, sales, customer service, asset management, financial accounting, human resources, and analytics interact within the SAP ERP application.

The course provides students with a broad basic knowledge of the core business processes, business interrelations, and integration of business processes in SAP ERP.

At the end of the course, students take a certification examination. If they pass the examination, they receive an SAP certificate, which is a fully recognized qualification in the industry.

10-day training: 

in the moring: theory
in the evening: laboratory

last day: SAP certification 
3 hours
multiple chioce and multiple responce questions
 

The course focuses on fundamental object-oriented design methods with an emphasis on design patterns and model driven concepts. The students learn to recognize, to know when to use, and to apply design patterns in varying situations in the context of an evolutionary development process. Furthermore the ability of an axiomatic rule base application of patterns, within a model driven approach, are discussed.

The lecture will take the form of seminars with exercises.