Business Informatics: Curriculum

Course description

In this sub-module, students acquire basic knowledge in the areas of external and internal accounting.

Methodology

Flipped Classroom

Learning outcomes

After passing this course successfully students are able to ...

• to describe the system of double-entry accounting,
• book simple business transactions,
• prepare annual financial statements,
• analyse annual financial statements on the basis of key figures,
• explain the system of corporate taxation,
• explain the elements and tasks of cost accounting,
• list the system components of cost accounting,
• determine the manufacturing costs of products and draw up an optimal production and sales programme.

Course contents

• Accounting
• Bookkeeping
• Balance sheet analysis
• Value added tax
• Taxation of profits
• Cost accounting

Prerequisites

none

Literature

• Wala, Baumüller, Krimmel: Accounting, balance sheet and taxes, Facultas
• Wala: Compact cost accounting, Amazon
• Wala, Siller: Exam training cost accounting, bookboon
• Wala, Felleitner: Written training in accounting & finance, Bookboon

Assessment methods

• Interim tests: 10 points
• Final exam: 90 points

Anmerkungen

Details see Moodle course

Course description

In this sub-module students acquire basic knowledge in the fields of normative, strategic and operational management.

Methodology

Flipped Classroom

Learning outcomes

After passing this course successfully students are able to ...

• distinguish between different types of corporate goals,
• distinguish between strategic and operational management,
• explain tasks and instruments of controlling,
• describe the advantages and disadvantages of a strong corporate culture,
• develop strategies for a company from the analysis of strengths, weaknesses, opportunities and threats,
• analyse the advantages and disadvantages of different forms of organizational structure,
• optimize business processes,
• distinguish between intrinsic and extrinsic motivation,
• distinguish between different leadership theories,
• explain the tasks and instruments of human resources management.

Course contents

• Management
• Company goals
• Corporate Culture
• Strategic management
• Organization
• Change Management
• Motivation and Leadership
• Personnel Management
• Controlling

Prerequisites

none

Literature

• Wala, Grobelschegg: Kernelemente der Unternehmensführung, Linde

Assessment methods

• Interim tests: 10 points
• Final exam: 90 points

Anmerkungen

Details see Moodle course

Course description

This course focuses on the students' self-responsible learning processes and imparts appropriate learning strategies as well as techniques and methods of time and self-management. It serves the students as a forum to get to know their group colleagues and prepares them for their own teamwork by applying and reflecting on selected team concepts.

Methodology

Impulse lecture, self-study (short videos, literature, etc.), discussion, work in groups, presentation

Learning outcomes

After passing this course successfully students are able to ...

• aquire learning content in a variety of ways (repertoire) and prepare it for easy access (e.g. structures, visualizations, etc…), thereby taking into account the functioning of the brain
• prioritize activities based on various methods (e.g. ABC-analysis, Pomodoro-technique) and plan their timing
• recognise personal stress triggers and behaviour patterns and develop and describe possibilities for pattern interruptions
• explain phase models of team development (e.g. Tuckman) and team roles (e.g. Belbin) and derive interventions for their own practice

Course contents

• Learning, learning models and learning techniques
• Self- and time management
• Constructive handling of stress
• Teamwork: tasks, roles, development

Prerequisites

none

Literature

• Franken, Swetlana: Verhaltensorientierte Führung – Handeln, Lernen und Diversity in Unternehmen, 3. Aufl. 2010
• Lehner, Martin: Viel Stoff – schnell gelernt, 2. Aufl. 2018
• Seiwert, Lothar: Wenn du es eilig hast, gehe langsam: Wenn du es noch eiliger hast, mache einen Umweg, 2018
• Van Dick, Rolf / West, Michael A.: Teamwork, Teamdiagnose, Team-entwicklung, 2. Aufl. 2013

Assessment methods

• Exercise, case studies, test, written exam

Anmerkungen

none

Course description

In the Technical English course, students will expand their language toolkit to allow them to effectively record and apply technical vocabulary and terminology in the context of future engineering topics such as automization, digitalization, machines and materials and 3D Printing. Moreover, students will advance their technical verbal and written skills by creating technical object and technical process descriptions specifically for technical professional audiences and engineering purposes.

Methodology

small and medium tasks and activities; open class inputs and discussion; individual task completion settings; peer review and discussion

Learning outcomes

After passing this course successfully students are able to ...

• record and employ technical vocabulary
• create and understand technical process instructions
• identify and produce technical text types according to their intended audience and communication purpose (for example a technical article and a process description)

Course contents

• Future Trends in Technology (automization, digitalization, machines and materials, 3D printing, AI, and the internet of things.)
• Visualizing technical descriptions
• Describing technical visualizations
• Technical object descriptions
• Technical process descriptions
• Technical English talk

Prerequisites

B2 level English

Literature

• Murphy, R. (2019). English Grammar in Use, 5th Edition. Klett Verlag.
• Oshima, A., Hogue, A. (2006). Writing Academic English, 4th Edition. Pearson Longman.

Assessment methods

• 25% Technical Process Description Group Task
• 25% Technical Process Description Language Task
• 50% in-class writing (25% writing / 25% applied knowledge)

Course description

This course deals with fundamentals and the most relevant skills of data management. Therefore, the first part addresses relational database systems. Precisely students learn how to create data models and design database schemas from them. Consequently, database hands-on skills are exercised using a software product. In the second part of the course learn how to manage data with the most common data formats and how to record and explore time series data with a NoSQL database.

Methodology

In the on-site sessions, brief lectures on selected topics of data management are given. Students need to prepare for each session in which hands-on skills are practiced. At the end of the course, each participant must pass a computer-based exam in which the achievement of the learning outcomes is assessed.

Learning outcomes

After passing this course successfully students are able to ...

• give an overview of database technologies and its applications, argue for different DB architectures and explain basic concepts of relational databases.
• design a logical data model for a given scenario using entity-relationship-modelling and derive a database schema from it
• design a relational database from a given data model and under consideration of relevant principles as well as assess the quality of the database schema according to the normal forms
• create and alter a database, insert data into it and manipulate database entries with simple or complex transactions
• run simple and complex queries on a database and create views and indices
• create, browse and transform XML and JSON-based data
• record and explore time series using a NoSQL database

Course contents

• Fundamentals of Database Systems
• Data Modelling and Database Design
• Data Quality and SQL Basics
• Data Manipulation and simple SQL Queries
• Complex SQL Queries and advance Database Concepts
• Data Formats XML and JSON
• NoSQL Databases

Prerequisites

None

Literature

• Elmasri, R. und Navathe, S.B. (2017). Fundamentals of Database Systems (7..Aufl.). Pearson.

Assessment methods

• Ongoing assessment through tests (Moodle quizzes, SQL exercises), Bonus points 10%
• Final exam (theory and practical skills), 100%

Course description

This course first introduces fundamental questions of Business Informatics (BI): occupational areas of BI, meaning and processes of a company, basics of information systems. Next, students will learn the relevant modeling techniques of the business process modeling area. Further emphasis will be given to the process of software selection and introduction. For their implementation, students will employ UML Use Case diagrams and specifications on the basis of given system requirements.

Methodology

During the on campus phases tests will be done, short inputs of the actual learning contents will be given and the exercise part A of the actual exercise will be solved together. In the self-study phases students solve the exercise part B of the actual exercise and prepare themselves for the following on campus phase by reading the relevant teaching and learning materials.

Learning outcomes

After passing this course successfully students are able to ...

• relate the fields of activities of business informatics to the the organization of an enterprise.
• indicate and explain, given a practical task, adequate solution methods of the business informatics.
• model the organizational structure of a company by an Organizational Chart and to model the operational structure of a company by a Process Map.
• abstract business processes based on given problem situations and to model them by business process models (Value-Added Chain Diagram, Process Map, (extended) Event-Driven Process Chains, and Business Process Diagram).
• derive, model and describe Use Cases based on system descriptions.
• recognize and define relationships between business processes of a company and their support by information systems.
• evaluate and select software based on defined criteria.

Course contents

• Core tasks of Business Informatics (BI)
• Companies from BIs perspective
• Fundamentals of modeling - model theory
• Business process modeling (eEPC, BPMN)
• Use Case Diagram and Use Case Specification
• Software selection and implementation
• From the business processes to the software system

Prerequisites

There are no prerequisites required.

Literature

• Study letters and presentations, as well as exercises and tests are compulsory literature for this course.
• Allweyer, T. (2005): Geschäftsprozess-management – Strategie, Entwurf, Implementierung, Controlling, W3L-Verlag
• Hanschke, I./Giesinger, G. /Goetze, D. (2010): Business Analyse - Einfach und Effektiv
• Hansen, R. (2009): Wirtschaftsinformatik 1 – Grundlagen und Anwendungen. Verlag: UTB. 12. Auflage
• Rupp, C. / Zengler, B. / Queins, S. (2004): UML 2 Glasklar, Carl Hanser Verlag, 3. Aufl

Assessment methods

• 6 tests to at max. 20 points (do not have to be passed positive)
• 1 intermediate exam to at max. 20 bonus / compensation points (does not has to be passed positive)
• 7 exercises to at max. 20 points (do not have to be passed positive)
• 1 end exam to at max. 60 points (has to be passed positive)

Anmerkungen

-

Course description

The course „Mathematik für Computer Science 1“ is supposed to convey mathematical skills and a structured mode of thought. The methods acquired by the students, based on a sustainable foundation, enable them to solve up-to-date technical and engeneering problems in an efficient and comprehensible way and to analyze established solutions. The emphasis lies on discrete mathematics and calculus.

Methodology

Both face-to-face learning (lecturing, practical exercises) and self-study (preparation and post-processing) are integrated.

Learning outcomes

After passing this course successfully students are able to ...

• to properly formulate mathematical statements using propositional logic and set theory, to represent numbers in various numeral systems, and to apply number operations using modular arithmetics
• to analyze basic properties of functions in one variable, and to interpret these in the appropriate subject context
• to apply operations and changes of representation with complex numbers, and to interpret them geometrically in the complex plane
• to examine sequences and series with respect to convergence
• to perform basic operations in differential calculus, to examine functions using differential calculus (with respect to extreme values and curvature behaviour) and to approximate functions locally in terms of Taylor polynomials
• to compute definite, indefinite and improper integrals
• to interpret definite integrals as areas or accordingly in the relevant context

Course contents

• Logic and sets, number sets and numeral systems
• Introduction to elementary number theory
• Relations, functions
• Complex numbers
• Sequences and series
• Differential calculus
• Integral calculus

Prerequisites

none

Literature

• Tilo Arens, Frank Hettlich, Christian Karpfinger, Ulrich Kockelkorn, Klaus Lichtenegger und Hellmuth Stachel: Mathematik. Springer Spektrum (aktuell: 4. Auflage 2018)

Assessment methods

• The basis for the assessment are 10 (online) quizzes, two units of practical exercises and two written tests. The qualitative criteria for practical exercises and tests are an appropriate understanding of the contents and the necessary mathematical skills.

Course description

A programming beginners' course in Java.

Methodology

Self-study interleaved with face-to-face classes.

Learning outcomes

After passing this course successfully students are able to ...

• solve simple problems with structured Java programs
• construct regular expressions and use them in Java programs
• develop text-based console applications capable of reading, sorting, searching and displaying collections of structured data records in various formats using elements of structured programming in Java
• create and execute blackbox tests
• perform and explain basic operations in arrays, lists, stacks, queues, and (binary) search trees
• adapt reference implementations of common data structures and algorithms for a given task/problem in Java
• select suitable data structures and algorithms for a given task/problem and evaluate their time complexity in Big-O notation

Course contents

• flow charts
• variables & primitive data types
• expressions
• control structures
• functions
• regular expressions
• sorting and searching
• debugger
• blackbox tests
• compund data types, arrays, lists, stacks, queues, (binary) trees, graphs

Prerequisites

Highschool Math. Basic computer skills.

Literature

• - Christian Ullenboom: Java ist auch eine Insel. (Rheinwerk Verlag)
• - Aditya Bhargava: Grokking Algorithms: An illustrated guide for programmers and other curious people. (Manning Publications)
• - Joshua Bloch: Effective Java (3rd Edition). (Addison-Wesley Professional)
• - Sedgewick: Algorithmen in Java. (Addison-Wesley)
• - Solymosi: Grundkurs Algorithmen und Datenstrukturen in JAVA (Springer)
• - Abts: Grundkurs JAVA (Springer)
• - Beneken: Grundkurs Informatik (Springer)

Assessment methods

• Final Test (80pts)
• Final Project (20pts)
• Exercises (10 bonus pts)

Anmerkungen

Just as learning a second language, it is by far no easy task to learn a programming language. It requires studying vocabulary and grammar as well as phrases and a lot of speaking, reading and writing practice until you are able to express your own ideas and thoughts in the new language. The effect of practicing with people that speak the language (and also correct you) cannot be overestimated, which is why a tutorial, held by 3rd semester students, can be installed in addition to regular classes. All beginners are hereby strongly advised to attend these tutorials.

Course description

In this Business English course, students will learn how to write clear, compelling, professional text, as well as, expanding their language toolkit to enable them to record and apply business vocabulary and terminology in the context of future trends in Business and Engineering. These trends would include, amongst others, diversity and inclusion, the globalization of the economy and, also, the internationalization of finance. Moreover, students will advance their verbal and written English language skills by applying critical thinking tools in the creation of impact analyses specifically for technical business audiences of the global community.

Methodology

small and medium tasks and activities; open class inputs and discussion; individual task completion settings; peer review and discussion

Learning outcomes

After passing this course successfully students are able to ...

• record and employ vocabulary for business in technology
• create a business technology impact analysis
• articulate both orally and in written form the different ways in which technology impacts business
• use specific vocabulary and terminology in, for example, leading a meeting

Course contents

• Business in Technology (for example finance and investment, the global economy, digital marketing and sales, international teams, and diversity and inclusion)
• Impact Analyses for Business and Technology
• Business English Talk

Prerequisites

B2 level English

Literature

• Murphy, R. (2019). English Grammar in Use, 5th Edition. Klett Verlag.

Assessment methods

• 25% Business Impact Analysis Group Task
• 25% Business Impact Analysis Language Task
• 50% in-class writing

Course description

This course introduces the process of finding ideas by testing various creativity techniques, whereby the students also act as moderators using appropriate moderation techniques. As part of the course, students deal with the phenomenon of "complexity", develop a systemic attitude and train the explanation of complex issues, especially for people without major technical expertise.

Methodology

Impulse lecture, self-study (short videos, literature, etc.), discussion, work in groups, presentation

Learning outcomes

After passing this course successfully students are able to ...

• moderate a map query followed by clustering and multi-point querying
• Implement case-oriented approaches to the generation of ideas (e. g. lateral thinking, critical thinking) as well as selected creativity techniques (e. g. stimulus word analysis, morphological box) to be explained and applied)
• adopt a systemic mindset and explain and apply tools for dealing with complexity (cf. B. Effectiveness structures, paper computers
• explain complex technical issues in a target group-specific manner (also for non-technicians)

Course contents

• Moderation of groups
• Brainstorming and creativity
• Networked thinking, dealing with complexity
• Explain complex issues

Prerequisites

none

Literature

• Dörner, Dietrich: Die Logik des Misslingens: Strategisches Denken in komplexen Situationen, 14. Aufl. 2003
• Lehner, Martin: Erklären und Verstehen, 2018 (e-Book)
• Rustler, Florian: Denkwerkzeuge der Kreativität und Innovation – Das kleine Handbuch der Innovationsmethoden, 9. Aufl. 2019
• Schilling, Gert: Moderation von Gruppen, 2005
• Vester, Frederic: Die Kunst vernetzt zu denken, 2002

Assessment methods

• Exercise, case studies, test

Anmerkungen

none

Course description

This course offers an introduction to Austrian business law with a focus on private law

Methodology

Lecture, self-study, discussion, exercises, case studies, inverted classroom

Learning outcomes

After passing this course successfully students are able to ...

• describe the structure of the legal system and the relationship between european law and national legislation
• explain the most important private law framework conditions in business life (e.g. legal subjectivity, contract law, representation, default, damages, etc.) and to be able to estimate their influence on business decisions
• take into account the special characteristics of B2B business transactions (e.g. obligation to notify defects, etc.) as well as those of B2C business transactions (e.g. consumer protection law, etc.);
• find legal sources (e.g. court rulings) using databases like the Legal Information System of the Federal Government and to research further relevant literature
• deal with a legal text and to interpret it on the basis of the canon of interpretation of legal methodology
• meet the requirements of trade law necessary for a specific business activity
• conclude contracts
• assess simple legal issues and to decide whether professional support - such as the involvement of a lawyer or notary – is necessary
• weigh up the advantages and disadvantages of different legal forms in the course of establishing a company

Course contents

• Legal system
• European fundamental freedoms
• Trade Law
• Legal forms
• Company register
• Law of Contracts
• Consumer protection law
• Disruptions in performance (default, warranty)
• Tort Law

Prerequisites

None

Literature

• Brugger, Einführung in das Wirtschaftsrecht. Kurzlehrbuch, aktuelle Auflage

Assessment methods

• Written Exam: 70%
• Interim tests and cases: 30%

Anmerkungen

None

Course description

In this sub-module students acquire basic project management skills.

Methodology

Flipped Classroom

Learning outcomes

After passing this course successfully students are able to ...

• define the term "project"
• classify projects by means of suitable criteria
• divide the project life cycle into different phases with different tasks
• differentiate between different procedure models, to formulate project goals regarding performance, costs and deadlines
• document requirements in a requirement specification as well as a functional specification in a comprehensible way
• distinguish between different forms of project organization and outline their respective advantages and disadvantages
• to differentiate between different project roles
• identify professional and social skills of project staff as an essential prerequisite for successful project work
• identify relevant stakeholders and their expectations of the project
• outline instruments for developing a beneficial project culture, to design countermeasures for unacceptable project risks
• draw up project plans (e.g. (e.g. work breakdown structure plan, schedule, time schedule, cost plan, etc.)
• apply project controlling methods and instruments (e.g. earned value analysis, etc.) for the purposes of schedule and cost control
• evaluate the effects of changing conditions and customer requirements
• moderate a project final meeting and write a project final report
• self-critically reflect on the achieved project results (e.g. (e.g. lessons learned etc.) and to derive improvement potentials for future projects in the sense of knowledge transfer
• present and defend project results to project stakeholders
• differentiate between program and portfolio management, to use project management software (Project Libre)

Course contents

• Project characteristics
• Project term
• Project types
• Project Management
• Procedure models
• Project goals
• Project requirements
• Phase and milestone planning
• Project Organization
• Project roles
• Project Structure Planning
• Estimate of expenditure
• Process and time scheduling (e.g. bar chart, network diagram)
• Resource and cost planning
• Project controlling and reporting
• Project completion
• Stakeholder Management
• Risk Management
• Project Marketing
• Quality Management
• Document Management
• Configuration Management
• Change Management
• Contract Management
• Management of project teams
• Agile project management
• Scrum
• Program Management
• Portfolio Management
• Project Management Software
• International Project Management
• Project Management Certifications

Prerequisites

None

Literature

• Timinger, Schnellkurs Projektmanagement, Wiley

Assessment methods

• Project work: 50%
• Interim tests: 50%

Anmerkungen

Details see Moodle course

Course description

The course „Mathematik für Computer Science 2“ is supposed to convey mathematical skills and a structured mode of thought. The emphasis lies on linear algebra and higher dimensional calculus.

Methodology

Both face-to-face learning (lecturing, practical exercises) and self-study (preparation and post-processing) are integrated.

Learning outcomes

After passing this course successfully students are able to ...

• to solve basic problems in general vector spaces and simple geometric problems in two and three dimensional euclidean space
• to perform elementary matrix operations, and to compute determinants and inverse matrices
• to solve systems of linear equations using Gauß‘ algorithm
• to perform geometric operations in terms of linear mappings
• to compute scalar products, orthogonal projections and orthogonal transformations, and to interprete them geometrically
• to compute eigenvalues, eigenvectors and eigenspaces
• to compute partial derivatives of functions with several variables, in particular to compute gradient, Hesse matrix and directional derivatives, and to determine local extrema of a scalar field
• to compute multiple integrals

Course contents

• Vector spaces
• Matrices and linear operators
• Systems of linear equations
• scalar product and orthogonality
• eigenvalues and eigenvectors
• Differential calculus with several variables
• introduction to multiple integrals

Prerequisites

none

Literature

• Tilo Arens, Frank Hettlich, Christian Karpfinger, Ulrich Kockelkorn, Klaus Lichtenegger und Hellmuth Stachel: Mathematik. Springer Spektrum (aktuell: 4. Auflage 2018).

Assessment methods

• The basis for the assessment are 10 (online) quizzes, two units of practical exercises and two written tests. The qualitative criteria for practical exercises and tests are an appropriate understanding of the contents and the necessary mathematical skills.

Course description

Building upon your Basic Programming knowledge we explore the basics of object-oriented programming and modelling.

Methodology

Self-study interleaved with face-to-face classes.

Learning outcomes

After passing this course successfully students are able to ...

• Explain princliples of object-orientation (Inheritance, Polymorohism, Encapsulation) with examples
• Explain class, interface, generics with examples
• Give an overview of selected abstract data structures (Collections) and explain their operations
• Model simple simple problems with class and interaction diagrams
• Model simple associations between classes in class diagrams
• Model program flow involving multiple classes with an interaction diagram
• Implement simple classes
• Re-implement behaviour of concrete super-classes in concrete (sub-) classes
• Implement given class diagrams in a programming language
• implement and use sortable and searchable data strucutres for concrete classes
• Export and import data to/from text-files with streams and correct exception handling
• Make use of basic operations of code versioning systems in coding projects

Course contents

• classes and objecte
• Inheritance, Polymorohism, Encapsulation
• abstract classes
• interfaces
• generics
• collections
• UML class diagrams
• UML interaction diagrams
• Object Oriented Programming (Classes, Objects, Reference, Inheritance, Polymorphism, Interfaces, inner classes)
• Exceptions and Exception handling
• Basics of code versioning systems

Prerequisites

First semester courses, especially 1. Structured Programming Lab (SPL) 2. Introduction to Business Informatics(EWI) 3. Data management (DM)

Literature

• Martina Seidl, Marion Scholz, Christian Huemer, Gerti Kappel: UML @ ClassroomAn Introduction to Object-Oriented Modeling. (Springer)
• Brahma Dathan, Sarnath Ramnath: Object-Oriented Analysis,Design and ImplementationAn Integrated Approach. (Springer)
• Christian Ullenboom: Java ist auch eine Insel. (Rheinwerk Verlag)
• Robert Sedgewick, Kevin Wayne: IntroductiontoProgramming in Java - An Interdisciplinary Approach. (Addison-Wesley)
• Schiedermeier: Programmieren mit Java (Pearson)

Assessment methods

• Exams (paper and/or tool based, closed book, 100 points): MidTerm Exam (Modelling Tasks, approx. in course week 5, 60 min, 30 points) Final Exam (Modelling & Programming Tasks, end of semester, 150 min, 70 points)
• Assignments (10 bonus points in total, all assignments equally weighted): 2 Hand-ins (Modelling) 1 Workshop (peer review activity) 6 Programming Assignments

Course description

This course provides a theoretical and practical overview of agile project management basics and covers in detail the selected agile process models Scrum and Kanban.

Methodology

Integrated course with self-study and on-site teaching components.

Learning outcomes

After passing this course successfully students are able to ...

• to assess the use of agile and classic process models in software development and to be able to select the appropriate development process
• plan and implement Scrum projects
• plan and implement Kanban projects

Course contents

• Agile Basics: Software Life Cycle(SLC) modell; Development processes (sequential, iterative, agile, hybrid) and areas of application; Changes in the project (Stacey Matrix); Differences between classic and agile project management; The agile manifesto and the 12 principles
• Scrum: Methods of effort estimation; Agile effort estimation Planning Poker; Scrum development method; Agile scaling frameworks
• Kanban: process model; visualization and WIP limit; service classes; Kanban cadences (regular meetings)

Prerequisites

none

Literature

• Agile Practice Guide; PMI Institute – Agile Alliance; 2017; Project Management Institute, Pennsylvania
• Erfolgsfaktor Agilität; Janko Böhm; 2019; Springer
• Kanban für die Softwareentwicklung; Thomas Epping; 2011; Springer

Assessment methods

• Learning tasks
• Intermediate tests
• Final exam

Course description

The course addresses an overview of software lifecycle (SLC) in general and provides further insights in selected phases of SLC. Tools supporting a collaborative setting in SLC are an important part of the course.

Methodology

project based learning, in-class and distance learning, weekly scheduled hand-ins, review discussions

Learning outcomes

After passing this course successfully students are able to ...

• select and manage tools to support SLC concerning requirements,
• perform requirements elicitation and persist tool-based requirements,
• develop and manage tool-based source code in a team,
• create and initiate rudimentary deployment pipelines,
• formulate quality criteria and prepare test plans.

Course contents

• Selected tools of diverse complexity to support SLC
• Tool-based methods for requirements elicitation
• Collaboration tools and source code management tools
• Deployment pipelines
• Integration of tests in pipelines
• Basic DevOps topic

Prerequisites

Basic java programming skills (semester 1) , basic project management skills (agile methods in particular)

Literature

• Sommerville, I., 2018. Software Engineering, 10., aktualisierte Auflage. it - informatik. Pearson, Hallbergmoos.
• Kim, G., Humble, J., Debois, P., Willis, J., 2017. Das DevOps-Handbuch: Teams, Tools und Infrastrukturen erfolgreich umgestalten, 1. Auflage. O’Reilly, Heidelberg.

Assessment methods

• Course-immanent performance evaluation
• Final exam

Course description

Based on IT requests for proposal, a project has to be set up for the selection of a Content Management System (CMS) including its installation and configuration at the customer's system environment (FHTW environment). The aim is to use the CMS to support the company's relevant business processes by the selected software system. This supports the networking and application of interdisciplinary subject areas (project management, business process management and modeling, software system modeling and benefit analysis) from the previous and current semesters of the study degree program in the context of a software selection project.

Methodology

In the on-campus phases, students have to solve quizzes, short inputs are given on the current course contents by lecturers, and feedback on the current project status is given on the one hand by the supervisors and on the other hand from students to students by peer reviews. In the self-study phases students have to further develop the software selection project, as well as to read the learning materials of the following presence phase and project task.

Learning outcomes

After passing this course successfully students are able to ...

• plan a real project (vision, work breakdown structure, project schedule etc.).
• carry out a real project (record keeping, teamwork, end presentation etc.).
• conduct a business analysis to support business processes of a company by a software system.
• analyze software requirements and model them by a Use Case Diagram.
• define the criteria for the selection of a Content Management System (CMS).
• create a benefit analysis based on defined selection criteria.
• carry out the customizing of selected CMS processes.

Course contents

• development of a project plan
• define a three-part project vision
• identify and describe stakeholders
• create simple work breakdown structures and timetables
• identify and model business processes
• derive, document and visualize customer requirements from business processes
• define a system specification
• identify, weight and evaluate software selection criteria
• carry out a market research on the basis of a criteria catalogue
• selection of a CMS software based on a benefit analysis
• installation, configuration and customizing a CMS

Prerequisites

Prior knowledge from courses in the ongoing second semester and the previous first semester of the study degree program is required on relevant topics such as presentation techniques, project management, business process modeling, software system modeling, as well as software selection, and benefit analysis.

Literature

• For this case study no separate teaching materials are used, but reference is made to teaching and learning materials from previous and current courses of the study degree program that are relevant to the implementation of the case study tasks.

Assessment methods

• Group assessment based on the software selection project:
• Project management (max. 20 points)
• Test (max. 10 points)
• Company analysis (max. 15 points)
• Software selection process (max. 15 points)
• CMS test installations (max. 10 points)
• Benefit analysis (max. 10 points)
• Final presentation (max. 10 points)
• Overall impression (max. 10 points)

Course description

In this course, students will learn basic concepts of probability calculus and applied statistics, utilizing the R software environment.

Methodology

integrierte Lehrveranstaltung, Fernlehre

Learning outcomes

After passing this course successfully students are able to ...

• solve combinatorial problems (permutations, combinations)
• compute probabilities for the occurence of certain events
• explain the relationship between random variables and probability distributions
• comprehend the operating mode of statistical tests, in particular to perform a simple statistical test and interpret the results
• calculate point and interval estimators
• perform the specified tasks within the R software enviroment

Course contents

• Basics of probability calculus
• Combinatorics
• Random variables
• Discrete and continuous probability distributions
• Expected value and variance
• Statistical tests
• Confidence intervals

Prerequisites

Basic knowledge of mathematics on high school level

Literature

• G. Teschl, S. Teschl (2014): Mathematik für Informatiker 2: Analysis und Statistik, Springer

Assessment methods

• in-class computer tests, final exam

Anmerkungen

-

Course description

Students learn about the definition of business processes and the use of business processes in an organization. Based on different aspects, students also learn to assess, model and document business processes.

Learning outcomes

After passing this course successfully students are able to ...

• assess and describe business processes
• model business processes (e.g. with EPC)
• discuss relevant aspects of organization-wide business process management
• develop a business process handbook
• apply methods of process assessment and process description
• improve processes

Course contents

• Assess and define business processes
• Describe relevant aspects of business processes (e.g. inputs, outputs, KPIs, …)
• Model business processes
• Create process maps
• process handbook
• business process management handbook

Prerequisites

None

Literature

• slides

Assessment methods

• Course immanent assessment

Course description

ERP systems are integrated software applications supporting organizational core activities (e.g., procurement, manufacturing and sales). This course addresses the managerial background, as well as the technical foundations and main functionalities using the software application MS Dynamics NAV 2018 as an example.

Methodology

Short lectures, Workshops, Exercises, Distance Study, Project

Learning outcomes

After passing this course successfully students are able to ...

• reproduce managerial background of procurement, manufacturing and sales.
• compare architectures of ERP systems and to discuss managerial and technical pros and cons.
• sketch a simplified data model for parts of an erp system.
• state and explain dependencies for information objects in the standard workflows procurement, manufacturing and sales.
• solve concrete tasks in material requirements planning (netting, lot sizing) and to implement them in NAV.
• explain the different steps in capacity and materials requirement planning, as well as their integration, using an example.
• calculate the production cost of a simple product, and to implement this in NAV.
• discuss pros and cons of ERP systems (using NAV) in a specific scenario.
• implement a self-chosen scenario in a given company in NAV.

Prerequisites

Business Process Modelling (with BPMN), Data Modeling, Cost Accounting

Assessment methods

• Exercises
• Multiple-Choice-Tests
• Project
• Final exam (Theory)
• Software exam (open book)

Anmerkungen

The software "MS Dynamics NAV 2018" is supplied and must be installed (or used within a virtual machine) on the own laptop.

Course description

In this course, the practical execution of posting tasks up to the trial balance in an IT system is taught and practiced.

Methodology

Short Presentations, Computer Sessions

Learning outcomes

After passing this course successfully students are able to ...

• Setup accounts and VAT on an accounting system
• Post opening book entries
• Work with accounts payable, accounts receivable
• Record common transactions
• Manage open items
• Handle common tasks at year-end like provisions, depreciation, accruals and deferrals
• Work with reports like balance list, account sheets
• Setup a trial balance and a profit and loss statement

Course contents

• Common transactions
• Year-end tasks
• Profit and loss statement, balance
• Setup and accounting system

Prerequisites

Financial Accounting

Assessment methods

• 6 Home Works (40 points)
• Use case (60 points)

Course description

Regularly companies make decisions about investments. There is a need of evaluating investments. Moreover you have to select the best investment option. Besides, it is necessary to find out the best way to finance these investments.

Methodology

Integrierte LV

Learning outcomes

After passing this course successfully students are able to ...

• understand the basics of interrelations between source and application of funds
• explain different types of finance
• calculate the effective yield of a zero bond
• apply static and dynamic investment-calculations
• calculate the net present value of machine which is intended to buy
• carrying out a cash flow statement

Course contents

• budgeted balance sheet
• Basics of mathematics in finance
• types of finance
• internal financing
• equity financing
• debt financing
• methods to calculate investments
• performance budget
• financial plan

Prerequisites

- Fundamentals of bookkeeping - Basics of cost accounting

Literature

• Geyer, Alois / Hanke, Michael / Littich, Edith / Nettekoven, Michaela (2012): Grundlagen der Finanzierung, 4. Auflage, Linde Verlag, Wien.
• Kruschwitz, Lutz (2014): Investitionsrechnung, 14. Auflage, Verlag De Gruyter, Oldenbourg.
• Thommen, Jean-Paul / Achleitner, Ann-Kristin (2012): Allgemeine Betriebswirtschaftslehre, 7. überarbeitete Auflage, Gabler Verlag, Berlin.
• Wöhe, Günter / Bilstein, Jürgen (2013). Grundzüge der Unternehmensfinanzierung, 11., überarbeitete Auflage, Vahlen Verlag, München

Assessment methods

• Course immanent assessment method (100%)

Anmerkungen

Could you please work through all exercises and questions of the script till page 56 before the first lesson.

Course description

This course introduces software architectures.

Learning outcomes

After passing this course successfully students are able to ...

• discuss the need for software architectures
• assess influencing factors to architectural decisions
• use methodical and constructive architectural aspects during a software development process
• identify relevant interfaces and building blocks during the archtectural process
• discuss basic architectural principles and their relevance for architectural decisions
• select and implement architectural styles based on requirements

Course contents

• aspects of architectures
• requirements influencing archtectures
• layers of architectures
• roles and tasks of an architect
• interaction with other roles
• architectural styles
• design principles
• software patterns
• software architecture as process
• design of software architectures

Course description

This course covers basic methods for developing (mobile) web applications along the full stack. This includes the development of frontends with base technologies like HTML5 and CSS3, as well as frameworks (e.g. Bootstrap). By use of PHP and the database management system MariaDB, key concepts for server-side programming on the backend and associated technologies are explained. Current trends and developments are discussed.

Methodology

lectures and supported exercises, presentation of exercises and discussion

Learning outcomes

After passing this course successfully students are able to ...

• design and implement static web pages based on standardized technologies (HTML, CSS)
• implement websites using CSS and clearly separate layout, structure and content
• integrate parts of other developers and add CSS Frameworks like Bootstrap to own web projects
• design and implement dynamic web pages using PHP as an example of server-side programming
• use general concepts of server-side programming (sessions, data transfer, authentication) for own projects
• easily acquire additional knowledge in the field of server side web programming if necessary
• understand the concept of sessions and cookies with implement it via PHP.
• connect to a database via PHP and set up CRUD statements.
• name technologies within the full stack and apply them correctly.

Course contents

• Fundamentals of website development
• HTML5 for describing websites
• CSS3 for layouting and graphical design, Bootstrap Framework
• General concepts of server-side programming
• Based on PHP: Passing (Form-)Parameters, Sessions & Cookies, Fileoperations
• PHP Programming
• Database linkage
• Full Stack Development
• SEO, Accessibility, Usability

Prerequisites

-

Literature

• see Moodle

Assessment methods

• see Moodle
• Exercises
• Project
• Tests

Course description

In this sub-module, students deepen, expand and cross-link the business management skills taught in previous semesters within the course of a business game.

Methodology

Flipped Classroom

Learning outcomes

After passing this course successfully students are able to ...

• formulate value-oriented corporate goals
• differentiate between strategic and operative business decisions
• optimally coordinate the various marketing policy instruments
• evaluate the advantages of investments using suitable calculation methods
• develop an optimal production and sales program
• weigh up between in-house production and external procurement
• conduct a break-even analysis
• calculate balance sheet ratios for the interpretation of financial statements
• identify rationalization potentials and take appropriate measures to realize them
• deal with large amounts of information in a structured way

Course contents

• Strategic Management
• Accounting
• Balance Sheet Analysis
• Procurement Management
• Production Management
• Marketing
• Investment Planning
• Cost Accounting

Prerequisites

Fundamentals of Business Administration

Literature

• Wala, Grobelschegg: Kernelemente der Unternehmensführung, Linde-Verlag

Assessment methods

• Immanent performances (100%)

Anmerkungen

Details see Moodle course

Course description

In this course, typical internal accounting tasks (cost accounting, financing, controlling) are carried out with the help of software.

Methodology

Workshops, Exercises

Learning outcomes

After passing this course successfully students are able to ...

• analyse annual financial statement using key business figures
• calculate cash flows
• apply core concepts of cost accounting (e.g. cost type acc., cost center acc., cost unit acc.)
• prepare investment decisions
• create a budget

Course contents

• state-of-art spreadsheet calculation
• practical implementation of internal accounting tasks
• business decision calculations

Prerequisites

Management Accounting Investment & Financing

Assessment methods

• 2 interim tests (25 points)
• 1 final exam (50 points)

Course description

"Einführung in Statistical Learning" is targeted on establishing a basis for the utilization of Statistical Learning methodology, showcasing four standard methods related to that framework. Statistical Learning brings together statistical and machine learning concepts and - as continuation of the "Statistische Datenanalyse" course - the course will exhibit additional possibilities to analyze data which are not based on the classic principles of inferential statistics, i.e., testing, estimation, and modelling. By means of classification methods, it will also be made clear that the main focus is not on explanation, but on prediction.

Learning outcomes

After passing this course successfully students are able to ...

• visualize and cluster multivariate data.
• apply classification methods and assess the quality of prediction.
• summarize the findings in a structured report.

Course contents

• Naive Bayes and k-nearest-neighbors classification, spineplot, spinogram, doubledecker plot
• resampling methods
• performance evaluation based on the confusion matrix
• hierarchical cluster analysis, distance measures, dendrograms, banner plot
• nonhierarchical cluster analysis, scree, elbow and silhouette plot

Prerequisites

Mathematics 1 & 2 Applied probability and statistics Statistical data analysis

Literature

• Datenanalyse und statistische Modellierung (D. Meyer, M. Wurzer)
• R. Hatzinger, K. Hornik, H. Nagel, M. Maier: R – Einführung durch angewandte Statistik (2. Auflage), Springer, 2014

Assessment methods

• Final exam: Write a comprehensive statistical report
• Students get additional points for exercises in class an Moodle minitests

Course description

"Statistische Datenanalyse" is targeted on providing a hands-on introduction to the applied analysis of empirical data. Students will gain an understanding of the need to be able to select the correct statistical method for a given problem and will learn how to execute the corresponding analysis step by step, i. e., reading and manipulating data as well as applying descriptive and inferential statistical methods. A special focus is on the interpretation and communication of analysis results by means of statistical reports. The "Literate programming"-approach guarantees the reproducibility of results, imperative in modern research. In order to show that data used for statistical analyses are the result of a structured process, the course also covers the main features of empirical social research.

Learning outcomes

After passing this course successfully students are able to ...

• explain main tasks of statistics and relate them to real-world tasks.
• understand mode of operation and requirements of empirical social research.
• preprocess, describe and visualize data in R.
• carry out hypothesis tests for categorical and metric variables.
• test associations between two categorical or two metric variables.
• establish and check regression model for metric variables.
• perform basic time series analyses.

Course contents

• fundamentals of empirical social research (design, sampling)
• data management in R
• one categorical variable: absolute and relative frequencies, bar charts, chi-squared test
• wo categorical variables: contingency tables, grouped bar charts, spine plots, chi-squared tests for independence and homogeneity
• one metric variable: histogram, indicators for mean and variance, boxplots, t-test
• two metric variables: scatter plot, correlation analysis, regression analysis
• time series analysis: time series plots, regression models, naive forecasting
• Reproducible Scientific Research: Literate Programming using R Markdown
• choosing the appropriate statistical method for a given problem

Course description

This course introduces the development of component-based (in particular service-oriented) software systems.

Methodology

Lectures, homework / project work and self-study with practical examples and supervised project work

Learning outcomes

After passing this course successfully students are able to ...

• implement component-based systems using a selected programming language
• implement service-oriented systems using a selected programming language
• analyzing existing monolithic systems and converting them into flexible, distributed systems
• exchange data asynchronously between (sub)systems using message queues, file transfer, RPC or shared databases
• encapsulate data layer functionalities using O/R Mappers and make them available using interfaces
• consider and apply design principles in the context of object orientation in the programming process

Course contents

• Component Based System Engineering
• Service-oriented System Components
• Various principles of system design
• SOA related to system components
• UML modeling (component/sequence diagrams)

Prerequisites

Basics in software development with a selected programming language. Basic knowledge of software architecture.

Literature

• see Moodle

Assessment methods

• Multimodal:
• Theoretical assessment (Moodle MC test)
• Homework (Coding Hand-Ins)
• Project work

Course description

The first part of the specialization "App & Web Development" tackles the devlopment of mobile Android applications.

Learning outcomes

After passing this course successfully students are able to ...

• develop advanced applications for the Android platform using appropriate tools
• discuss typical design patterns and best practices for the development of Android applications
• implement own projects using these patterns

Course contents

• Development of Android smartphone applications
• Design patterns for Android Applications
• Android Application Design (user interface, threading, web services, data persistence)
• PItfalls and best practices (memory management, memory leaks, debugging, crash-logs, performance)

Prerequisites

programming, web engineering.

Course description

The second part of 'App & Web Development' covers the development of iOS based applications.

Methodology

Slides, links and documents for Self-studying. Topics and questions will be discussed in class and implementations will be shown. Small assignments after each class.

Learning outcomes

After passing this course successfully students are able to ...

• develop advanced iOS applications using the current development tools and IDEs
• name and explain advanced design patterns and best practices for developing iOS applications
• structure and build your own iOS application implementations according to these design patterns and best practices

Course contents

• Development of iOS based applications
• Design patterns for iOS apps
• Basic skills in programming language Swift
• Design of iOS apps (Coding UI, Threading, Web Service access, Persistence)
• Pitfalls and proven methods.

Prerequisites

Knowledge in object oriented programming.

Assessment methods

• Small assigments after each class.
• Theory exam at the end of the semester.

Course description

This in-depth course focuses on data handling in heterogeneous environments with a wide variety of data types (from structured to unstructured, from continuous and discrete data to text data) with a special focus on Big Data environments. This course is part 2 of a series on Big Data & Data Science topics ("Big Data & Data Science" consisting of Big Data Infrastructure, Big Data Engineering, Data Science, Machine Learning). After completing the entire series, students can independently build and assess a continuous Big Data workflow.

Methodology

Content is taught in a flipped classroom methodology, i.e. students independently acquire new topics, and in the attendance phase this content is deepened and practiced with practical examples.

Learning outcomes

After passing this course successfully students are able to ...

• understand the differences between data types and data formats in order to process data in a targeted manner.
• retrieve data from web sources (websites and provided interfaces)
• read and process larger data sets using Apache Spark
• further process structured and unstructured data using Spark SQL
• elaborate advantages of different data architectures (Lambda and Kappa)
• control the workflow of data and to apply processing steps in a targeted manner

Course contents

• data in big data environments
• WebScraping, REST-APIs
• Apache Spark
• Kafka
• Nifi

Prerequisites

The course assumes data management, Python knowledge as well as the contents of the course "Big Data Infrastructure" and is itself a prerequisite for the advanced course Data Science.

Literature

• Kleppmann, M., 2017. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Revised Edition. ed. O’Reilly UK Ltd., Boston.
• Luu, H., 2021. Beginning Apache Spark 3: With DataFrame, Spark SQL, Structured Streaming, and Spark Machine Learning Library, 2nd ed. ed. Apress, S.l.
• Estrada, R., 2018. Apache Kafka Quick Start Guide: Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applications. Packt Publishing, Birmingham Mumbai.

Assessment methods

• short Moodle-Tests
• exercises
• final project

Course description

This course teaches fundamentals and basic skills for technologies with a special focus on big data. Prior to this, necessary skills in dealing with operating systems (Linux), DevOps engineering (Git, Docker), programming languages (Python) and development environments (Jupyter Notebook) are taught. This course is part of a series on Big Data & Data Science topics ("Big Data & Data Science" consisting of Big Data Infrastructure, Big Data Engineering, Data Science, Machine Learning). After completing the entire series, students can independently build and assess a continuous Big Data workflow.

Methodology

Content is taught in a flipped classroom methodology, i.e. students independently acquire new topics, and in the attendance phase this content is deepened and practiced with practical examples.

Learning outcomes

After passing this course successfully students are able to ...

• use Linux basic commands for practical tasks, import or manage files in a Linux system
• pull content from a Git repository and deploy services using containers
• use the main commands and data structures of the Python programming language, as well as develop executable code in the form of Python programs and Jupyter notebooks
• read data from CSV files and manage Jupyter notebooks in a version-controlled manner
• store and retrieve structured, semi-structured, and unstructured data using NoSQL database technologies
• provide an overview of the dimensions and challenges of big data and plan the distribution of data and computational operation on a Hadoop cluster
• understand the use of a Hadoop cluster and understand it through simple examples
• store data distributed on a Hadoop cluster and process it using Hadoop's own methods
• apply the technologies learned in the course combined for an exemplary scenario to perform computations for a dataset on a Hadoop cluster

Course contents

• Linux, Git and Docker
• Python and Jupyter Notebooks
• Data storage and NoSQL
• Big Data Introduction
• Hadoop Basics

Prerequisites

The course assumes data management and programming skills and is itself a prerequisite for the in-depth course Big Data Engineering.

Literature

• Leornardo, C., 2020. Docker: Docker for the Absolute Beginner. Independently published.
• Loeliger, J., McCullough, M., 2012. Version Control with Git: Powerful tools and techniques for collaborative software development, 2nd ed. O’Reilly and Associates, Beijing.
• Meier, A., Kaufmann, M., 2019. SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management, 1st ed. 2019 Edition. ed. Springer Vieweg, New York, NY.
• Kunigk, J., George, L., Wilkinson, P., Buss, I., 2019. Architecting Modern Data Platforms: A Guide to Enterprise Hadoop at Scale, 1st Edition. ed. O’Reilly UK Ltd., Beijing China ; Sebastopol, CA.

Assessment methods

• short Moodle-Tests
• exercises
• final project

Course description

The course teaches skills to customize the ERP system Navision to your own needs. Simple adaptations include, for example, the appearance and the possibilities provided to the respective role to work with the program. If an extended functionality is required, it is not enough to make an adjustment, adaption on the databasis of Navision and in the application logic is necessary. These topics will be taught in the course by providing examples. To implement new functionality in Navision, the internal programming language C/AL is used. In addition to learning the programming language and the procedure for supplementary programming, a new client is created and existing data is entered. The handling of data will also be covered in the topic of interfaces. (How external systems can exchange data with Navision). The final part is the report creation (visual representation of interesting data) and the integration of the report in the role center of the respective user role. Students gradually learn the structure of the ERP system, thereby understanding how it works and better understand the internal processes, such as which data sources are changed, where this data is stored and how it can be accessed. In the course of creating the visual representation of data in the form of an input and output mask, the overall understanding of the structure of the program becomes apparent. Students are thus able to display their own information, but also to configure existing views in such a way that the workflow can be simplified. The transfer of knowledge is directly visible and tangible, as it is very easy to make your own adjustments (for example to text, positioning, display, additional tabs, ...). The understanding of the handling of the database and the presentation forms the basis for the supplementary programming, where the understanding of the internal processes of Navision are necessary to develop own functionality. This specialized knowledge, which goes beyond the application, is always needed in practice

Methodology

Lectures and guided exercises, live demonstration, project work

Learning outcomes

After passing this course successfully students are able to ...

• describe the data model (table structure) of the ERP system MS Dynamics Navision.
• to make different adjustments to the appearance of the ERP system MS Dynamics Navision
• create additional functionality in MS Dynamics NAV with the C/AL language using the Dynamics development environment and integrate it into the system.
• connect different systems to MS Dynamics using selected connectors to allow access from outside the ERP system.
• perform data migration (import existing data, for example, from legacy systems)
• create reports (visual representation of data of interest) and integrate them into the ERP system
• create a new client (perform minimal configuration)
• create new users in the ERP system, assign roles and rights and create individual views for roles

Course contents

• Basics architecture and structure of MS Dynamics Navision
• Dealing with the development environment: debugging, code creation
• C/AL programming language
• Implement extensions in MS Dynamics Navision
• Configuration of the ERP system (client setup, data import and migration)
• Dealing with the development environment: debugging, code creation
• Connect ERP system via web interface (OData & SOAP)

Prerequisites

ERP Basics Basic programming knowledge

Assessment methods

• Homework
• Projektwork
• Project presentation

Course description

Project-based and process-controlled selection of ERP systems

Methodology

blended learning case study

Learning outcomes

After passing this course successfully students are able to ...

• plan, coordinate and control the selection of an ERP system using project management methods, taking into account operational conditions.
• use selected methods of business process management (process mapping, business process master list, business process modelling) to analyze the as-is organization, to identify potentials and to describe the target picture.
• to describe the standard selection process (procedure, methods) and to adapt it to the operational conditions.
• to systematically develop a set of criteria for the ERP system selection and to use it in the various stages of the selection process (shortlist/longlist) according to the situation.
• to conduct the selection decision in the process based on methods (benefit analysis, AHP) and to evaluate the strengths/weaknesses of the methods used.
• to plan, organize and to perform a negotiation workshop based on a predefined script.
• to support the selection decision at different stages based on cost and investment analysis (TCO, ROI).
• to identify and evaluate the requirements for configuration and customizing based on a FIT/GAP analysis.

Course contents

• ERP systems (basics, benefits, market overview)
• organizational analysis (organizational structure, process organisation)
• system selection (Process, methods)
• set / catalogue of criteria (reference)
• optimizing the set / catalogue of criteria (cost/benefit analysis, analytic hierarchy process)
• cost and investment analysis
• Fit/Gap Analysis
• project management in ERP projects
• process models in ERP projects

Prerequisites

Course: Introduction to Business Informatics Course: Business process analysis and modeling

Literature

• Gronau, N., 2010. Enterprise Resource Planning. Architektur, Funktionen und Management von ERP-Systemen. 2. Auflage. München: Oldenbourg Wissenschaftsverlag GmbH
• Kurbel, K., 2003. Produktionsplanung und –steuerung – Methodische Grundlagen von PPS-Systemen und Erweiterungen. 5. Auflage. München.
• Hesseler M., Görtz M., 2008. Basiswissen ERP-Systeme. W3L-Verlag, 1. Auflage, Witten
• Jansen, M. 2014. Nutzwertanalyse – wenn Entscheiden schwerfällt. VDI. ERFA-Kreis Nürnberg/München
• Becker, J., Vering, O., Winkelmann, A. (2007). Softwareauswahl und Einführung in Industrie und Handel – Vorgehen und Erfahrung mit ERP- und Warenwirtschaftssystemen. Springer Verlag Berlin

Assessment methods

• Individual: mid-term exam
• group: case study

Course description

This second part of the specialization "Business Digitalization" extends the "Process Automation" course to the IT support inter-company processes (in particular customers and suppliers)

Methodology

In the course, a case study on the digitization of a company is processed against the background of embedding in a corporate network (e.g. via the supply chain). The processing starts with the creation of a digitalization strategy, digitalization roadmap up to the ("hands-on") automation of business processes by means of BPA and RPA tools - with the aim of integration across company boundaries.

Learning outcomes

After passing this course successfully students are able to ...

• assess the potentials of digitalization and automization in the transformation of digital companies
• identify inter-company processes suitable for automization
• identify process and data interfaces between companies
• select technologies for data exchange between companies

Course contents

• Models for organizing and optimizing intercompany processes
• Business Process Automation (BPA) and Robotic Process Automation (RPA) in the context of company networks

Prerequisites

Process Automation

Literature

• Venkatraman, N. (1994). IT-enabled business transformation: From automation to business scope redefinition. Sloan management review, 35, 73–73.
• Krumay, B., Rueckel, D., & Koch, S. (2019). Model for Strategic Positioning in Transformative Situations. Proceedings of ICIS 2019 – International Conference on Information Systems, 1–17.
• Beetz, R., & Riedl, Y. (2019). Robotic Process Automation: Developing a Multi-Criteria Evaluation Model for the Selection of Automatable Business Processes. 25th Americas Conference on Information Systems, AMCIS 2019, Cancún, Mexico, August 15-17, 2019. https://aisel.aisnet.org/amcis2019/enterprise_systems/enterprise_systems/4
• Lehnert, M., Röglinger, M., & Seyfried, J. (2018). Prioritization of Interconnected Processes. Business & Information Systems Engineering, 60(2), 95–114. https://doi.org/10.1007/s12599-017-0490-4
• Wanner, J., Hofmann, A., Fischer, M., Imgrund, F., Janiesch, C., & Geyer-Klingeberg, J. (2019). Process Selection in RPA Projects—Towards a Quantifiable Method of Decision Making. In H. Krcmar, J. Fedorowicz, W. F. Boh, J. M. Leimeister, & S. Wattal (Hrsg.), Proceedings of the 40th International Conference on Information Systems, ICIS 2019, Munich, Germany, December 15-18, 2019. Association for Information Systems. https://aisel.aisnet.org/icis2019/business_models/business_models/6

Assessment methods

• Case study (70%), knowledge check (30%)

Course description

This first course of the specialization "Business Digitalization" deals with one of the most important topics of digital transformation: process automation, here limited to internal processes.

Methodology

In the course, a case study on the digitization of a company is worked on. The work begins with the creation of a digitization strategy and digitization roadmap and continues with the ("hands-on") automation of business processes using BPA and RPA tools.

Learning outcomes

After passing this course successfully students are able to ...

• Recognize digitization and automation as a tool in the transformation of businesses
• Apply process models for the digital transformation of companies
• Identify internal company processes that can be optimized by means of automation
• Identify potential for new in-house digital workflows
• Automate internal company processes for the purpose of optimization (using BPA and RPA)

Course contents

• Digitization, digitalization and digital transformation
• Models of business transformation
• Digitalization (optimization, automation) of business processes
• Business Process Automation (BPA) and Robotic Process Automation (RPA)
• Automation within the company by means of workflow management systems (for the implementation of BPA) and automation systems for RPA

Prerequisites

Business process engineering

Literature

• Krumay, B., Rueckel, D., & Koch, S. (2019). Model for Strategic Positioning in Transformative Situations. Proceedings of ICIS 2019 – International Conference on Information Systems, 1–17.
• Venkatraman, N. (1994). IT-enabled business transformation: From automation to business scope redefinition. Sloan management review, 35, 73–73.
• Han, P. F. (2013). Criteria, Use Cases and Effects of Information Technology Process Automation (ITPA). Advances in Robotics & Automation, 03(03). https://doi.org/10.4172/2168-9695.1000124
• Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital Business Strategy: Toward a Next Generation of Insights. MIS Quarterly, 37(2), 471–482. https://doi.org/10.25300/MISQ/2013/37:2.3
• Koch, C., & Fedtke, S. (2020). Robotic Process Automation: Ein Leitfaden für Führungskräfte zur erfolgreichen Einführung und Betrieb von Software-Robots im Unternehmen. Springer Vieweg.

Assessment methods

• Case study (70%), knowledge check (30%)

Course description

The second part of the immersion "UX Software Quality Assurance" covers the user centered design of user interfaces.

Methodology

Integrated course

Learning outcomes

After passing this course successfully students are able to ...

• explain the design lifecycle
• explain and apply design methods
• develop user interfaces iteratively using approved methods
• develop low and high fidelity prototypes using appropriate tools

Course contents

• prototyping
• design methods & patterns
• 4 dimensions of a prototype
• prototyping tools

Prerequisites

BWI-4-BB - Usabilty Evaluation

Assessment methods

• Assignments
• Project assigments

Course description

The first part of the immersion "UX & Software Quality Assurance" covers the evaluation of software with regard to usability.

Methodology

Integrated course

Learning outcomes

After passing this course successfully students are able to ...

• give an overview of usability testing methods
• independently conduct selected evaluation methods (heuristic evaluations, tress testing, usability test)
• design evaluations according to scientific principles
• analyse test results and document them using standardized reporting templates
• explain the importance of accessibility and ethics in designing

Course contents

• psychological and technical basics
• planning, execution and analysis of heuristic evaluations, tree tests and usability tests
• preparation of test results for clients

Prerequisites

keine

Assessment methods

• Assignments
• Project assignments

Course description

In this course, the focus is put on frontend & backend development for web applications. Previously acquired knowledge and skills from the courses Web Technologies and Web Scripting will be applied and deepened in a specific web development project. The lecturers act as clients in order to simulate daily professional life for web developers. Regular sprint reviews are part of the course and represent the preparation for recurring meetings with the clients, which are also part of the professional life of web developers.

Methodology

Independent development of a web application. Teachers act as clients. During the self-study phases, sprints are carried out, which are reviewed during the classes.

Learning outcomes

After passing this course successfully students are able to ...

• independently develop a web application using front-end and back-end technologies

Course contents

• Deepening the contents from Web Technologies & Web Scripting

Prerequisites

Web Technologies & Web Scripting

Assessment methods

• Project planning (15%)
• Project execution (20%)
• Project results (50%)
• Project presentation (15%)

Course description

The course follows directly the contents of the "Webtechnologies" course and builds upon the already learnt basics of web application development. Script languages such as JavaScript and TypeScript are worked out and advanced state-of-the-art front-end frameworks such as jQuery are presented and used. The course primes for the follow-up courses "Web Frameworks" respectively "Web Development Project".

Methodology

lectures and guided exercises, programming assignments, mid-term tests and code discussions

Learning outcomes

After passing this course successfully students are able to ...

• integrate dynamic contents (user interactions, AJAX) into a web site via JavaScript.
• integrate and make use of parts of other developers and frameworks (e.g. Bootstrap, jQuery).
• apply the basics of web application development via TypeScript.
• link JS/TypeScript-based web frontends to backend components.

Course contents

• JavaScript, DynamicHTML, DOM (browser-side programming)
• dynamic loading of web contents via AJAX
• JavaScript-libraries and frameworks demonstrated via jQuery
• basics of TypeScript
• connection of web frontent to backend

Prerequisites

basics of web application development, client-server-infrastructures, HTML, CSS, working with HTML/CSS frameworks (see previous module "Webtechnologies")

Assessment methods

• Exercises
• Mid-term tests (moodle quizzes)
• practical mid-term test
• Project

Course description

After an introduction in classical marketing concepts, the course focuses on digital marketing methods.

Learning outcomes

After passing this course successfully students are able to ...

• Identify target groups and develop a marketing strategy
• describe, plan and implement relevant aspects of digital marketing
• distinguish between classical and digital marketing, as well as inbound and outbound marketing
• give an overview on digital marketing tools and to use them
• describe the customer life cycle and sales funnel, and to derive marketing decisions
• consider challenges of cross-channel marketing in marketing plans
• descfribe and implement growth hacking
• implement E-Mail marketing and content marketing

Course contents

• Target groups
• 4 P’s, 7 P’s, 4 C’s
• Digital Marketing, mobile Marketing
• Customer Lifecycle
• Growth Hacking
• Email Marketing
• Content Marketing
• Influencer Marketing

Course description

This course enables students to develop (mobile) web applications using current frontend web frameworks. Relevant web frameworks (such as Spring Boot, Symfony and FLASK) will first be presented, and an own project using Spring Boot implemented based on the framework-specific design and architectural principles. A REST-API will be implemented and authorized through JWT. Main focus will be given to practical work.

Learning outcomes

After passing this course successfully students are able to ...

• plan and implement dynamic web applications using server-side programming (using Spring Boot)
• use general concepts of server-side implementation (sessions, data transmission, authentification) for own projects
• implement and link data bases to web applications
• implement data exchange between client and server using Ajax and JSON
• implement maintainable software using selected frontend frameworks

Course contents

• Base technologies of webserver infrastructure
• Fundamentals of server-side programming (sessions, cookies, data exchange)
• Java Spring Boot Programming
• Interfacing Data Bases
• Provision of Restful Web Services

Prerequisites

Structured and OO Programming; Data Management; Web Engineering

Assessment methods

• Project Work

Course description

This course enables students to develop (mobile) web applications using current frontend web frameworks. Relevant web frameworks (such as React, Angular and Vue.js) will first be presented, and an own project using Vue.js implemented based on the framework-specific design and architectural principles. The integration with a REST-API will be implemented using Ajax; JSON will be used for data exchange. Main focus will be given to practical work.

Methodology

Short presentations; project work; self-study with practical examples; coaching.

Learning outcomes

After passing this course successfully students are able to ...

• give an overview of relevant frontend web frameworks and discuss pros and cons
• implement maintainable software using selected frontend frameworks
• implement data exchange between client and server using Ajax and JSON
• explain the architecture and the design principles of specific frameworks and to apply them in SW development
• deploy the implemented software

Course contents

• overview on relevant frontend frameworks
• architecture and design principles of selected frameworks
• components of a selected framework
• programming using a selected framework

Prerequisites

Structured and OO Programming; Data Management; Web Engineering

Assessment methods

• Project Work

Course description

The third part of the specialization "Big Data & Data Science" introduces data engineering and data visualization

Learning outcomes

After passing this course successfully students are able to ...

• import raw data from various sources (data bases, internet) in various formats
• preprocess raw data for further processing
• critically assess diagrams
• visualize data for exploration
• create interactive graphics

Course contents

• create data science projects using R studio
• manipulate data with the R tidyverse framework
• Fundamentals of visualization
• create meaningful diagrams using ggplot2
• create interactive diagrams

Prerequisites

Course: "Applied Probability and Statistics" Course: "Applied Statistics and Data Analysis"

Course description

The fourth part of the specialization "Big Data & Data Science" focuses on Machine Learning.

Learning outcomes

After passing this course successfully students are able to ...

• fit machine learning models (supervised, unsupervised) to data
• assess and compare the performance of predictive models
• get into new data science topics

Course contents

• Supervised Learning: Trees, Neural Networks, k-NN, Naive Bayes
• Unsupervised Learning: PCA, Medoid-Based Clustering, Association Rules
• Benchmarking and Tunining of machine learning algorithms
• Special Topics (Text Mining, Network Analysis)

Prerequisites

Course: "Data Engineering"; Course: "Applied Probability and Statistics"; Course: "Applied Statistics and Data Analysis"; Course: "Introduction to Statistical Learning"

Course description

The third part of the specialization "Business Applications" focuses on requirements engineering (also in an agile setting) and prepares for the IREB certification.

Learning outcomes

After passing this course successfully students are able to ...

• clearly separate system from context
• document requirements
• administer requirements
• identify, classify and administer sources for requirements (stakeholder, documentsl, systems)
• apply techniques for gathering requirements
• identify, analyse and solve conflicts during the requirements gathering process
• carry out context modeling
• model information structures (UML class diagrams)
• model dynamic aspects (Use cases, data flow diagrams, activity diagrams)
• model scenarions (sequence diagrams)
• consider functional requirements, contraints and quality requirements in agile projects

Course contents

• requirements engineering projects
• documentation
• requirements gathering techniques
• scenario modeling
• requirements of agile requirements engineering projects

Prerequisites

fundamentals of modeling (use cases, class diagrams)

Course description

The fourth part of the specialization "Business Applications" tackles the tool-based development of data base-intensive applications.

Learning outcomes

After passing this course successfully students are able to ...

• assess the advantage of No-Code/Low-Code applications vs. classic software development
• identify use cases for No-Code/Low-Code
• Choose a suitable NCLC development platform
• Using some platform (e.g., MS Power Apps), create simple business applications
• Apply security mechanisms
• Integrate the application with existing systems using interfaces

Course contents

• No-Code and Low-Code development platforms
• Functions of Appluication Builder
• Integration of DB applications into existing infrastructure
• security aspects

Course description

This course gives an overview on technical, managerial and legal aspects of cloud computing and enables planning, implementation and evaluation of native cloud- and migration projects, as well as the implementation of simple cloud applications.

Learning outcomes

After passing this course successfully students are able to ...

• evaluate pros and cons of various deployment models (on premise vs. diverse cloud alternatives) and choose the best one for a project
• evaluate Cloud Service Providers and applications according to suitable criteria, carry out a TCO calculation and select the best solution
• configure and monitor several instances in a public cloud environment
• develop owh applications in a Platform as a Service (PaaS) context

Course contents

• Cloud Computing NIST definition, architecture and deployment models
• Cloud Computing NIST definition, architecture and deployment models
• Hybrid Cloud Solutions
• Cloud Computing platforms & applications, basics of Cloud Application Development
• Economic aspects of Cloud Computing, Outsourcing, TCO calculations
• Legal aspects, cloud standards
• Selection of CSPs, Vendor Lock-In

Course description

The course tackles important infrastructure (Hardware and Software) for digital Enterprises, ranging from computing centers to smart devices while focusing on selection, planning and rollout of this infrastructure.

Learning outcomes

After passing this course successfully students are able to ...

• assess basic concepts of virtualization and container technologies
• plan a redundant computing center and the required hardware
• automate the rollout of infrastructure using Infrastruce as Code (IaC) and document and monitor it using a coinfiguration managment data base (CMDB)
• define criteria for hardware tender procedures
• describe use cases for smart devices in companies

Course contents

• Data Center Basics
• Server, Storage and Networking hardware and protocols
• Scalability and Redundancy
• Virtualization and different hypervisors, Virtual Machines vs. Container technologies
• Infrastructure as Code (IaC) and configuration management, CMDBs and IT documentation, Monitoring
• Smart Devices and equipment (e.g., cameras, drones, sensors)
• Hardware procurement
• Planning, Design and Rollout of enterprise IT infrastructure

Course description

The third part of the specialization "UX & Software Quality Assurance" tackles Software Testing in an agile setting.

Learning outcomes

After passing this course successfully students are able to ...

• describe and use proper software testing terminology
• describe the fundamental testing process and actively apply from a users' perspective
• describe and apply IT standards of software testing (e.g., IEEE 829)
• apply fundamental testing methods
• plan and carry out simple test automatization using unit tests and UI-driven development
• explain principles of agile sofware development
• explain the challenges of testing and quality assurance in agile projects
• carry out and support suitable testing activities in agile teams

Course contents

• testing principles
• testing planning
• testing
• testing documentation
• agile methods of testing

Course description

The fourth part of the specialization "UX & Software Quality Assurance" adresses software quality management and deployment.

Learning outcomes

After passing this course successfully students are able to ...

• discuss basics of quality criteria
• apply quality measures in practice
• explain quality standards (e.g. IEEE) and apply aspects of them
• Visualize core software quality criteria for decision making
• assess the importance of software
• carry out a risk assessment for software projects
• explain the principles and advantages of devops and the relationship to quality management
• Discuss culturall aspects of devops (communication, collaboration, integration, automatisation)
• practice roles, teams and project structures related to DevOps
• Plan steps for the implementation of DevOps in a use case

Course contents

• quality management
• quality standards
• risk assessment
• DevOps

Course description

The course offers an overview of the fundamentals of IT security and deals with cryptographic methods, authenticity, key management, access control and secure communication.

Learning outcomes

After passing this course successfully students are able to ...

• to name the protection goals of IT security and to show threats as well as methods to guarantee the goals
• know cryptographic methods and can name their respective strengths and weaknesses and thus possible application scenarios
• Encrypt and sign emails and any documents
• List methods for access control and monitoring at network, system and application levels and explain their function and application scenarios
• Can explain basic technologies for secure communication
• Explain basic procedures for evaluating the importance of systems or for risk analysis

Course contents

• Basics of Information Security
• Threat to IT security and sources of danger (internal and external threats)
• Basics of cryptography
• HMAC
• Public key infrastructures (PKI)
• Signatures
• Certificates
• access control
• Identification/Authentication/Authorization
• Password security/entropy
• DMZ, Firewall & IDS/IPS
• IPSec
• Transport Layer Security
• Secure communication mechanisms

Course description

Software security is the umbrella term for software designed to continue to function properly in the face of malicious attacks. Security as part of the software development process is an ongoing process involving people and processes that ensures the confidentiality, integrity and availability of the application. Secure software is the result of security conscious software development processes where security is built in and therefore software is developed with security in mind

Learning outcomes

After passing this course successfully students are able to ...

• Establish identity & access management in (web) applications
• Recognize the 10 most common security vulnerabilities in software
• Use established authentication methods (HTTP Digest, Single Sign On/SAML/OAuth2)
• Development of secure applications and assessment of current security risks
• Evaluate software projects using a Secure Software Lifecycle
• Assessment of threats to applications using a risk matrix
• Basics for conducting a security assessment / pentest
• Software development: Secure by design, secure by default

Course contents

• Application Security
• Secure by design principles
• Secure authentication in SW
• Web Application Security
• Identity & Access Management
• Risikobewertung in SW / Threat Modeling
• DB Security

Prerequisites

Knowledge of common web languages (HTML, JS, CSS, PHP, AJAX) Knowledge of object-oriented languages (Java || C#. / .net) Knowledge of handling databases (mySQL or Oracle) Basic knowledge of using Linux Knowledge of network protocols: Ethernet, IP/ARP, TCP/UDP, DNS, Application Layer protocols, Transport Layer Security or http/s, s/ftp, ssh,...

Literature

• SAML Specifications 2.1
• OAuth 2.0 Autorization Framework - RFC6749
• OWASP 10 2021++/--
• NIST Secure Software Development Framework
• OWASP Secure Coding Guideline

Course description

The course introduces the basics of communication and conversation and conveys possibilities of appropriate behavior in different professional communication situations (e.g. conflicts). In the course of the course, the students deal with the phenomenon of "culture" and develop action strategies for intercultural contexts.

Methodology

Via corresponding examples, case studies and workshop units, which essentially relate to the short videos.

Learning outcomes

After passing this course successfully students are able to ...

• Analyze communication behavior using relevant models (e.g. Schulz v. Thun, transaction analysis) and develop your own strategies for behavior that encourages conversation (e.g. rapport);
• to explain the different stages of a conflict (e.g. according to Glasl's escalation model) on a case-by-case basis and to develop appropriate options for action in conflict situations
• To explain levels of culture (e.g. behavior, beliefs) using concrete examples; Develop situationally appropriate options for action (intercultural competence) for dealing with cultural differences.

Course contents

• Communication and conversation skills
• Conflict management
• Cultural theory
• Interculturality

Prerequisites

none

Literature

• Doser, Susanne: 30 Minuten Interkulturelle Kompetenz, 5. Aufl. 2012
• Glasl, Friedrich: Selbsthilfe in Konflikten, 8. Aufl. 2017
• Greimel-Fuhrmann, Bettina (Hrsg.): Soziale Kompetenz im Management, 2013
• Weisbach, Christian-Rainer / Sonne-Neubacher, Petra: Professionelle Gesprächsführung, 9. Aufl. 2015

Assessment methods

• Course immanent

Anmerkungen

-

Course description

The academic work course prepares students for writing academic papers, especially the bachelor thesis.

Methodology

The integrated course consists of two parts: The online course deals with the basics of scientific work including basic statistics. The faculty-specific part introduces the peculiarities of their research fields and the concrete processing of related topics.

Learning outcomes

After passing this course successfully students are able to ...

• explain different types of scientific work.
• explain the standards that characterize scientific work.
• draft topics and formulate research questions.
• select and use working methods for the selected issues.
• structure a scientific work in a formally correct manner.
• write a proposal (synopsis, disposition) for a seminar or bachelor thesis.
• carry out (literature) research, evaluate sources and quote them according to scientific standards.
• explain and implement formal and linguistic requirements for a scientific text.
• znderstand representations of basic descriptive statistics and choose and apply sensible methods for your own questions.

Course contents

• Scientific criteria
• Knowledge generation methods and theories
• Types as well as structuring and construction of scientific papers
• Guidelines for Safeguarding Good Scientific Practice
• Searching for and narrowing down topics
• Research questions - their formulation, operationalization
• Source Acquisition Strategies
• Documentation of sources
• Proposal (exposé, disposition)
• Scientific writing style and basic lines of reasoning
• Formal design of academic papers
• Methods, areas of application and interpretation of descriptive statistical methods.

Course description

In this project course, students practice the main phases of the software lifecycle (requirements engineering, software design, implementation, testing, deployment).

Learning outcomes

After passing this course successfully students are able to ...

• plan and implement a software project in groups using engineering methods
• create a software requirements specification, or analyse an existing one
• plan and implement interfaces between (sub-)systems

Course contents

• Integration of skills from previous courses in the studies
• agile project management

Prerequisites

Software Lifecycle Management Agile Project Management Structured and OO Programming Software Architectures Distributed Systems Data Management Software Architectures Distributed Systems

Course description

The bachelor paper is an independent written work, which has to be written in the context of a course.

Learning outcomes

After passing this course successfully students are able to ...

• to apply the scientific methods in the respective subject correctly to a technical task and to reflect the results critically.
• to structure a scientific work in a formally correct way
• to conduct (literature) research, evaluate sources and cite them according to the usual scientific standards

Course contents

• The bachelor paper usually includes an independent examination with a detailed description and explanation of its solution.