Business Computer Science

Course content: Logic, sets, relations and functions, combinatorics, algebraic structures, number theory and modular arithmetic, basics of graph theory

Course content:

Part 1 Business administration:
Classification of business administration in the scientific disciplines; formal goals and substantive objectives of companies and their measurability through ratios; production factors; siting; legal forms of companies; co-operations and mergers of companies

Part 2 Economics:
Microeconomics: basic questions and methods, demand curve, theory of the firm, market theory (polypole, monopoly, oligopoly).
Macroeconomics: Objectives and drivers of economic policy, economic cycles, classical-neoclassical economic model, Keynesiantheory

Course content: Elementary data types; algorithmic thinking(computational thinking); imperative programming (assignment, conditional statements, loops); functions (static methods, parameters, return values, recursion); arrays; memory organisation, visibility and lifetime of variables; debugging and testing; classes, constructors, methods and attributes in Java as basic concepts of object orientation; introduction to UML (class and sequence diagrams, if applicable)

Course content: Basics of business computer science; basics of computer science (numeral systems, computer architecture, networks, algorithms and software); introduction to modelling data and processes and to simulation; introduction to business information systems

Course content: Basic situations in business world, e.g.: Introducing a company, negotiations, marketing, conferences, logistics, import/export, payment terms, business trips, complaints and advertising/sales; using tools such as grammars, internet sites, bilingual and monolingual dictionaries and specialised vocabulary to cope with language tasks

Course content: In terms of content, this module covers core topics of linear algebra, in particular: Vector spaces and their structure; vectors and linear mappings as basic elements of linear algebra; multiple representations and algebraic description of these elements, in particular of linear mappings by matrices; important linear mappings (including scalar products, geometric operations); core concepts of linear algebra (including linear (in)dependence, linear combination); important properties of linear mappings (including rank, kernel); linear systems of equations: Algorithms for solving, criteria for solvability; plus links to a selection of application areas (e.g. image and image processing, programming, data compression)

Teaching content: Financial target figures of private-enterprise companies;leverage (gearing) of borrowing funds; typical ratios of dynamic and static methods of investment analysis for security; security in financing; series of payments and effective interest rate for instalment, annuity, bullet loans, zero bond; minimum deposit, private liability and profit appropriation rules for shareholders of sole proprietorships, OHG, KG, GmbH, UG, AG (Ltd., PLC); self-financing and debt as well as internal and external financing; cash flows in the context of the cash flow statement; simultaneous financial and investment planning

Course content: In-depth object orientation (inheritance, abstract classes, interfaces; polymorphism and dynamic binding; modelling of associations between classes in UML; OO design principles); exception handling in Java (context of exception handling, checked and unchecked exceptions); genericity (generic classes and methods, type parameters); collections in Java (the limits of arrays, collection interfaces, use of collections); stream-oriented I/O in Java (e.g. file I/O, object or socket streams); lambdas and streams; threads; selected Java libraries (e.g. for programming graphical user interfaces, networking).E.g. file I/O, possibly object or socket streams); lambdas and streams; threads; selected Java libraries (e.g. for programming graphical user interfaces, network connections, database connection); case study (realising practical tasks against unit tests)

Course content: Algorithm concept (algorithm, determinism, finiteness, etc.); approaches to algorithm design; complexity; searching and sorting; dynamic data structures: list, tree, hash table; graphs and networks, algorithms for spanning trees, Dijkstra, A*

Course content: Basic concepts; basics of business process management; basics of business process modelling; simple and extended event-driven process chains; UML activity diagrams; business process model and notation; application systems for software-supportedmodelling of the above-mentioned modelling languages

Course content: Management of information systems; project definition; common project management (project initiation, project planning, project support, project completion); agile project management using Scrum as example

Course content: Decision theory, linear optimisation, graphical solution, duality theory, primal and dual simplex methods, transport problems, integer linear optimisation, network planning technology

Course content: Fundamentals and typology of industrial production; production and cost models with limitational and substitutional production conditions; production programme planning; programme-oriented demand planning; production and cost models with indirect production factor-product relationships

Teaching content: Operating system architectures; processes and threads; scheduling strategies; synchronisation and communication; memory management; structure, architecture and layer structure; services and protocols of ISO/OSI reference model; secure protocol architectures; network management

Course content: Terms in the context of software projects; procedure and process models in software development, in particular agile management; project planning and controlling; risk management; introduction to quality assurance and testing; modern tools to support various development activities; patterns in object-oriented design

Course content: Basic concepts and tasks of a database management system; database design (ER modelling / normalisation); basics of relational databases; Structured Query Language (SQL); views, rights management, integrity; transaction management; applications with databases

Course content: descriptive statistics; characteristics and visualisation of one- and two-dimensional frequency; time series; basic concepts of probability theory; one- and two-dimensional random variables; inferential statistics; simple point and interval estimates; basics of hypothesis tests (t-test, Fisher test, chi-square test)

Course content: Concept, tasks, requirements and organisation of controlling; instruments of operative controlling: full standard costing, contribution costing, integrated operational planning, break-even analyses, ratios and ratio pyramids

Course content:
Basics: System of the German legal system; basic concepts of European law;
Private law: conclusion of contracts; content of contracts, in particular warranties; types of contracts in the software market;
Consumer protection law: sale of consumer goods; information rights and withdrawal, e.g. for distance selling contracts;
Contracts for digital products: general terms and conditions; intellectual property law
Public law: constitutional principles; telecommunications law; data protection law

Course content: Students work on a typical software development projectin a team from definition of requirements to delivery. Students apply the course content, particularly from the programming and software engineering courses, using a practical example. Students also develop their soft skills in order to organise their work in a team and resolve any conflicts that arise. In periodical project meetings, the project supervisor from the university or company takes on the role of product owner, with whom open questions are clarified and to whom the project status is reported.

Course content: Building on the teaching content of Software Engineering 1 (focus on learning and implementing an agile development process), the phases of software engineering from requirements definition to maintenance are discussed further: classic and modern process and procedure models (waterfall, RUP, SaFE, DevOps) and their artefacts; requirements elicitation, including non-functional requirements; software architecture patterns; design and evaluation of software architectures; testing with a focus on non-functional requirements, acceptance tests; delivery, operation, maintenance of software and the associated infrastructure (virtualisation)

Course content: Data warehousing; data quality; OLAP; process models for data analysis; data visualisation; cluster analysis; association analysis; classifiers (e.g. decision trees, random forests, nearest neighbour, neural networks); regression (linear, robust); simple text mining; simple process mining

Course content: Conceptual basics of discrete-event simulation; stochastic basics (concepts, random variables, distributions, generation of random variables; confidence intervals and model fitting); process model for conducting simulation studies (description of objectives, task specification and modelling; data acquisition and preparation; experiment planning; implementation and evaluation; verification and validation); simulation tools; emulation and optimisation; introduction to a simulation tool (e.g. plant simulation); conducting a simulation study (as experimental work)

Course content: Working on a complex business computer science task in a regional company. Participants act as an external project team within this company.

Course content:
Part 1 Sales/Marketing: Definitions; marketing objectives; marketing strategies; marketing instruments (product, contracting, distribution and communication policy)
Part 2 Market research: Definitions, statistical basics; forms of data collection (surveys, observations, panels, experiments); data analysis methods (univariate, bivariate and multivariate data analysis methods)

Students select compulsory elective modules (WPF) with in total 10 CP from the following catalogues:

• From the modules of the Bachelor's degree programme inComputer Science:
  - Modules from the specialisations
  - Compulsory elective modules Programming (WPP)
  - Compulsory elective module Interdisciplinary Skills
  - Compulsory elective modules in Computer Science
• Subjects from the Bachelor's degree programmes of other faculties (on application)

Course content:
Part 1 ERP and WMS: Introduction to ERP systems; supply chain planning and collaboration; (strategic) IT management; process design(workflow management systems); conducting a case study aboutworkflow management systems
Part 2 Advanced Planning: Introduction to the use of solvers for math. optimisation; strategic network planning; master planning, production and procurement planning, route planning

Course content: Introduction, thematic assignment and overview(stakeholders, security policies, assets); Transport Layer Security (TLS/SSL): protocols, realisation as well as limits & attack options; design principles (protection of information, privilege classes, design patterns for secure applications, fail-safe defaults); scanning, net mapping & protection mechanisms; firewalling; vulnerabilities in software and OS attacks; SW protection according to BSI 200-1 and 200-2; selected BSI basic protection modules for IT and SW security

Course content: Become acquainted with a company's practice and structures; independent work on and documentation of a complex, longer-term project or part of a project related to business computer science; preparation of a case study as proof of the knowledge acquired or project worked on as a scientific paper

Independently working on and documention of a scientifically based project related to business computer science, thereby independently deepening existing theoretical knowledge