Kurse-eng

Over­view
Tracks
OR Modules
BA Modules
SCM Modules
Mar­ke­ting Modules
Digi­ta­li­sa­tion and Infor­ma­tion Sys­tems Modules
Finance Modules
Ethics Modules

Our Courses

Please find here an over­view of all modules that you can take in the Busi­ness Ana­ly­tics & Ope­ra­tions Rese­arch pro­gram. When selec­ting and desi­gning our courses, we always try to ensure that our courses sys­te­ma­ti­cally build on each other and do not overlap and. In this way, we ensure that our stu­dents estab­lish suc­ces­sive com­pe­ten­cies in the various methods and sub­ject areas during the course of their stu­dies.

Current

Our module con­tents are always geared to cur­rent topics from the busi­ness world. In addi­tion to lear­ning appro­priate methods for sol­ving common pro­blems, we regu­larly offer guest lec­tures.

Redundancy-free

When selec­ting our course con­tents, we make sure that there are no over­laps. This ensures that with each course you develop and learn some­thing new.

Coordinated

Our courses are arranged in such a way that struc­tured lear­ning is pos­sible. Some courses initi­ally pro­vide a theo­re­tical foun­da­tion, while others build on it. This allows that stu­dents develop a deep under­stan­ding of the indi­vi­dual sub­ject areas.

Example Tracks

Here you will find some examples of how you could build up your stu­dies to pre­pare for a cer­tain career path.

Example Track: OR Analyst

Semester I

In the first semester the basics of Ope­ra­tions Rese­arch and Decision Theory are taught. OPL enables you to imple­ment your own models and solve them using the soft­ware. In the intro­duc­tory course Simu­la­tion you will learn to carry out simu­la­tion stu­dies inde­pendently.

Semester II

The module Algo­rithms and Data Struc­tures extends exis­ting know­ledge about pro­gramming from the first semester. In the course Pro­gramming Heu­ris­tics you can apply this know­ledge. Sto­chastic Models and Plant Simu­la­tion in com­bi­na­tion with the course Simu­la­tion from the first semester pre­pare you for a pos­sible career as a simu­la­tion expert.

Semester III

In the third semester your know­ledge of methods is now at a very high level. It is time to put your skills to the test in a spe­cia­list area. Courses from the Supply Chain Manage­ment area are listed here as examples. In the seminar on Supply Chain Manage­ment and in the seminar on Ope­ra­tions Rese­arch you will write a sci­en­tific paper on a cur­rent rese­arch topic, sup­ported by our employees.

Semester IV

  • Master Thesis

In the fourth and last semester you will write your master thesis. For example, it could be a good idea to con­tinue your sci­en­tific work from the third semester.
Of course, there is also the pos­si­bi­lity to write your master thesis in coope­ra­tion with a com­pany. OR ana­lysts are very wel­come in com­pa­nies – also and espe­ci­ally during their master thesis.

Example Track: Data Scientist

Semester I

In the first semester important theo­re­tical basics of sta­tis­tics, as well as the imple­men­ta­tion in R, are taught. The ethics module tea­ches you important sci­en­tific and eco­nomic know­ledge of ethics.

Semester II

The courses in the 2nd semester deepen your know­ledge in R and bring you closer to important prac­tical app­li­ca­tions. It is also pos­sible to take a Data Sci­ence course which will make you an expert in the field of Data Sci­ence.

Semester III

In the third semester your know­ledge of fore­cas­ting methods will be deepened and you will learn methods of the field of data sci­ence. Algo­rithms and Data Struc­tures will also expand your exis­ting know­ledge of pro­gramming from the first two semes­ters. In the pro­ject module Busi­ness Infor­ma­tics you will write a sci­en­tific paper on a cur­rent topic of busi­ness infor­ma­tics and thus learn important know­ledge that will be hel­pful for your master thesis.

Semester IV

  • Master Thesis

In the fourth and last semester you will write your master thesis. For example, it could be a good idea to con­tinue your sci­en­tific work from the third semester.
Of course, there is also the pos­si­bi­lity to write your master thesis in coope­ra­tion with a com­pany. Data Sci­en­tists are very wel­come in com­pa­nies – also and espe­ci­ally during the master thesis.

Operations Research Modules

Here you can find all cur­r­ently offered courses in the Track Ope­ra­tions Rese­arch.

Operations Research

  • Man­datory Module
  • OR Module

The course pro­vides the con­cep­tual basis of Ope­ra­tions Rese­arch and gives an intro­duc­tion to mathe­ma­tical mode­ling (e.g. graph theory, linear models) of real busi­ness pro­blems. Based on this, dif­fe­rent opti­mi­za­tion methods are pre­sented (e.g. integer and com­bi­na­to­rial opti­mi­za­tion or dynamic opti­mi­za­tion). The aim of the course is to enable stu­dents to model and solve pro­blems inde­pendently.

Decision Science

  • Man­datory Module
  • OR Module
The course pro­vides metho­dical know­ledge for decision-making in various busi­ness situa­tions. One focus is on decisions under uncer­tainty. Depen­ding on the situa­tion, dif­fe­rent methods are used, which allow rational decision makers, given their pre­fe­rences, to make the best pos­sible choice among dif­fe­rent alter­na­tives. At the end of the course, stu­dents have an over­view of these pro­ce­dures and can apply them to busi­ness decision situa­tions.

Stochastic Models

  • Man­datory Module
  • OR Module

The module tea­ches dis­tri­bu­tion theo­re­tical basics and con­cepts of sto­chastic pro­cesses. Buil­ding on this, the mode­ling of sto­chastic pro­cesses (e.g. by Markow chains or queue models) is taught. The course enables stu­dents to model and ana­lyze sto­chastic sys­tems and pro­cesses inde­pendently.
In com­pa­rison to simu­la­tion, the models are solved ana­ly­ti­cally.

Simulation

  • Man­datory Module
  • OR Module

Since many years simu­la­tion has been one of the most important methods for stu­dying dynamic pro­cesses. Many invest­ments in pro­duc­tion and logistics are only made after appro­priate vali­da­tion through the use of simu­la­tions. In this course, our stu­dents learn the necessary metho­do­lo­gical know­ledge for the imple­men­ta­tion of simu­la­tion stu­dies and the prac­tical app­li­ca­tion of the simu­la­tion soft­ware (Any­Logic).

Operations Scheduling

  • Com­pul­sory Elec­tive Module
  • OR Module

The course pro­vides an in-depth under­stan­ding of the cur­rent methods and con­cepts of pro­cess plan­ning in mate­rial goods and ser­vice com­pa­nies. Based on mathe­ma­tical models describing a busi­ness pro­cess, stu­dents deepen their com­pe­ten­cies for the app­li­ca­tion of optimal solu­tion methods as well as heu­ris­tics for more com­plex models. The aim of the course is to pro­vide tech­nical com­pe­tence so that stu­dents are able to ana­lyze and model com­plex pro­blems inde­pendently and to solve them with a sui­table method.

Simulation with Plant Simulation

  • Com­pul­sory Elec­tive Module
  • OR Module

The module is an advanced course in the field of dis­crete event simu­la­tion and is aimed at stu­dents who are already fami­liar with the basics of simu­la­tion. This is fol­lowed by an intro­duc­tion to the simu­la­tion tool Plant Simu­la­tion. The course com­bines simu­la­tion with object-ori­ented pro­gramming to map pro­per­ties of com­plex sys­tems. At the end of this course, stu­dents will be able to inde­pendently create simu­la­tion models with indi­vi­dual con­trol algo­rithms.

Seminar on Operations Research

  • Com­pul­sory Elec­tive Module
  • OR Module
In this seminar, stu­dents learn and deepen the basics of sci­en­tific work. Using typical rese­arch methods, stu­dents inde­pendently pre­pare a sci­en­ti­fi­cally struc­tured pro­ject work and pre­sent their rese­arch results at the end of the course. In terms of con­tent, new and cur­r­ently rele­vant topics from the field of ope­ra­tions rese­arch are offered as rese­arch topics every semester.

Object-oriented programming of heuristics

  • Com­pul­sory Elec­tive Module
  • OR Module
This course rep­res­ents an advanced course in object-ori­ented pro­gramming with a focus on the imple­men­ta­tion of common OR pro­ce­dures. This includes e.g. Branch and Bound methods, but also heu­ris­tics like the Savings method. After this course, stu­dents will be able to imple­ment object-ori­ented OR pro­ce­dures in the Java pro­gramming lan­guage and apply them to real pro­blems.

Modeling and Optimization with OPL

  • Com­pul­sory Elec­tive Module
  • OR Module

In this course, stu­dents learn to rep­re­sent real pro­blems by mathe­ma­tical models and to solve them in CPLEX Opti­mi­za­tion Studio on the PC. Advanced tech­ni­ques of linear mode­ling and the use of the mode­ling lan­guage OPL are taught.

Business Analytics Modules

Here you can find all cur­r­ently offered courses in the Track Busi­ness Ana­ly­tics.

Service Analytics

  • Man­datory Module
  • BA Module

With the increa­sing impor­t­ance of ser­vices and digi­tiza­tion, data-based insights into customer pre­fe­rences and bene­fits are beco­ming increa­singly cen­tral to anti­ci­pa­ting customer needs and beha­viors and recom­men­ding or offe­ring the right pro­ducts or ser­vices. The course Ser­vice Ana­ly­tics deals with data ana­lysis methods for tasks in digital com­merce and customer inter­ac­tion. In par­ti­cular, the algo­rithms of modern recom­mender sys­tems are dis­cussed and eva­luated. In the exer­cise, stu­dents learn the lan­guage R and apply their know­ledge to prac­tical pro­blems, develop and test recom­mender sys­tems on rea­listic and large customer data sets.

Algorithms and Data Structures

  • Man­datory Module
  • BA Module
The course pro­vides a basic intro­duc­tion to the topic of algo­rithms. Dif­fe­rent con­cepts of algo­rithms, such as recur­sion, are taught in an app­li­ca­tion-ori­ented way using the Python pro­gramming lan­guage. In order to gain a better under­stan­ding of the rela­tion bet­ween the algo­rithm and its imple­men­ta­tion in the com­puter, basic data types, data struc­tures, and con­trol struc­tures are exp­lained first, fol­lowed by how that struc­ture influ­ences the algo­rithm. Finally, stu­dents learn eva­lua­tion methods for algo­rithms in the con­text of com­ple­xity theory. During the pro­gramming exer­cises, stu­dents gain insights into dif­fe­rent pro­gramming styles and deve­lop­ment envi­ron­ments.

Statistical Forecasting Methods

  • Man­datory Module
  • BA Module

Stu­dents get an over­view of the most important fore­cas­ting methods and models. They will also learn how to apply basic fore­cas­ting tech­ni­ques to prac­tical cases using the R soft­ware envi­ron­ment. The aim of the course is to enable stu­dents to under­stand and apply common fore­cas­ting models in a con­text-depen­dent manner and to inter­pret and cri­ti­cally ques­tion fore­casts.

Time Series Analysis

  • Com­pul­sory Elec­tive Modules
  • BA Module
The stu­dents acquire the metho­dical com­pe­tence and theo­re­tical basis of important prac­tice-rele­vant sta­tis­tical methods of time series ana­lysis and apply their know­ledge with the help of the soft­ware envi­ron­ment R.

Seminar Statistics

  • Com­pul­sory Elec­tive Module
  • BA Module

In this course, stu­dents learn how to prac­ti­cally solve a case using sta­tis­tical and/or data ana­lysis methods of sta­tis­tics. The focus is on metho­do­lo­gical ques­tions. In this course, stu­dents will write a seminar paper in order to demons­trate their com­pe­tences in sci­en­tific work and in their rese­arch tech­ni­ques.

Seminar Econometrics

  • Com­pul­sory Elec­tive Modules
  • BA Module

In this course, stu­dents learn how to solve a prac­tical case using eco­no­metric methods. The focus is on metho­do­lo­gical ques­tions. In this course, stu­dents will write a seminar paper in order to demons­trate their com­pe­tences in sci­en­tific work and in their rese­arch tech­ni­ques.

Quasi-experimental Policy Evaluation

  • Com­pul­sory Elec­tive Module
  • BA Module

In this module, stu­dents learn detailed methods of eco­nomic and eco­no­metric policy eva­lua­tion. Stu­dents will apply quan­ti­ta­tive tech­ni­ques to eva­luate cur­rent policy mea­sures in typical fields of eco­no­mics.

Data Science with R

  • Com­pul­sory Elec­tive Module
  • BA Module

In this course, stu­dents acquire the con­cep­tual and IT-tech­nical basics for the pre­pa­ra­tion and ana­lysis of data sets with the help of the inter­ac­tive sta­tis­tical soft­ware envi­ron­ment R. Based on example data sets, the stu­dents will solve eco­nomic pro­blems with the help of ade­quate tools and methods of data sci­ence. In addi­tion, the basics of SQL data­bases, MySQL and SQLite are taught.

Theoretical Foundations of Classical Statistics and Econometrics

  • Com­pul­sory Elec­tive Module
  • BA Module
In this module, stu­dents will inde­pendently study sub­ject lite­ra­ture on theo­re­tical sta­tis­tics and eco­no­metrics and thus deepen their pro­ba­bi­listic and sta­tis­tical metho­do­lo­gical com­pe­tence. In this module already exis­ting theo­re­tical basic know­ledge of sta­tis­tics and eco­no­metrics is deepened.

Reading course on statistics

  • Com­pul­sory Elec­tive Module
  • BA Module

In this module, book chap­ters or journal arti­cles on a selected sta­tis­tical topic are dis­cussed and cri­ti­cally ques­tioned. In this way, stu­dents develop cogni­tive abi­li­ties to acquire new know­ledge and new methods in the field of eco­no­metrics on their own.

Reading course on Econometrics

  • Com­pul­sory Elec­tive Module
  • BA Module

In this module, book chap­ters or journal arti­cles on a selected topic of eco­no­metrics are dis­cussed and cri­ti­cally ques­tioned. In this way, stu­dents develop cogni­tive abi­li­ties to acquire new know­ledge and new methods in the field of eco­no­metrics on their own.

Supply Chain Management Modules

Here you can find all cur­r­ently offered courses in the field of Supply Chain Manage­ment.

Configuration of Production and Logistics Systems

  • Com­pul­sory Elec­tive Module
  • SCM Module

Stu­dents gain an in-depth under­stan­ding of the cur­rent methods and con­cepts for con­fi­gu­ring pro­duc­tion and logistics sys­tems. They get to know the rele­vant quan­ti­ta­tive decision models and some prac­tice-rele­vant solu­tion algo­rithms and acquire the abi­lity to put the acquired know­ledge into prac­tice during the deve­lop­ment of plan­ning sys­tems.

Semninar on Supply Chain Management

  • Com­pul­sory Elec­tive Module
  • SCM Module
In this seminar, stu­dents learn and deepen the basics of sci­en­tific work. Using typical rese­arch methods, they inde­pendently pre­pare a sci­en­ti­fi­cally struc­tured pro­ject work and pre­sent their rese­arch results at the end of the course. In terms of con­tent, new and cur­r­ently rele­vant topics from the field of supply chain manage­ment are offered as rese­arch topics every semester.

Logistics: Inventory and Transport Management

  • Elec­tive Module
  • SCM Module
In this module, the basic ques­tions of logistics manage­ment will be dealt with. Dif­fe­rent approa­ches and opti­mi­za­tion methods in wareh­ousing and inventory manage­ment on the one hand and trans­port and route plan­ning, on the other hand, will be taught. Thus stu­dents learn to sup­port decisions in the ope­ra­tional prac­tice and to solve issues goal-ori­ented.

Supply Chain Business Game

  • Com­pul­sory Elec­tive Module
  • SCM Module

The course uses the busi­ness simu­la­tion game “The Fresh Con­nec­tion”. In this busi­ness game, stu­dents take up dif­fe­rent roles in a supply chain, inclu­ding purcha­sing, pro­duc­tion, logistics, sales and supply chain manage­ment, and make stra­tegic, tac­tical and ope­ra­tional supply chain decisions. In addi­tion, the stu­dents learn the cur­rent methods and con­cepts of plan­ning and con­trol in the supply chain and expe­ri­ence the effects of decisions on the busi­ness suc­cess of a com­pany.

Supply Chain Planning

  • Com­pul­sory Elec­tive Module
  • SCM Module
The course exp­lains the con­cep­tual struc­ture of supply chain plan­ning in the com­pany and its imple­men­ta­tion in Advanced Plan­ning Sys­tems (APS). The course pro­vides the basic con­cepts, models, and methods used in AP sys­tems and clas­si­fies them regar­ding the common plan­ning matrix. Stu­dents learn how to handle AP sys­tems using the SAP APO system as an example and expe­ri­ence the pos­si­bi­li­ties and limi­ta­tions of decision sup­port by AP sys­tems in busi­ness prac­tice.

Service Operations

  • Com­pul­sory Elec­tive Module
  • SCM Module

This course focuses on quan­ti­ta­tive methods of ser­vice ope­ra­tions and revenue manage­ment as well as on their app­li­ca­tion in the ser­vice industry, e.g. with air­lines, car rental com­pa­nies, tour ope­ra­tors and accom­mo­da­tion pro­vi­ders. In ser­vice ope­ra­tions, the main focus is on ali­gning demand and capa­city and on opti­mi­zing ser­vice pro­cesses. Within the frame­work of revenue manage­ment, the con­cepts of price dif­fe­ren­tia­tion, capa­city con­trol, over­boo­king con­trol, and dynamic pri­cing are dealt with.

Modeling and Analysis of Retail Operations

  • Com­pul­sory Elec­tive Module
  • SCM Module

The course pro­vides an over­view of cur­rent methods and con­cepts in the field of retail ope­ra­tions. Decision models and ana­ly­tical methods are dis­cussed, which are used in retail prac­tice for pro­blem ana­lysis and decision sup­port. In this con­text, the cur­rent deve­lop­ments in online retail, multi-channel retail and/or omnich­annel retail will also be dis­cussed.

Marketing Modules

Here you can find all cur­r­ently offered courses in the field of mar­ke­ting.

Analytical Customer Management

  • Com­pul­sory Elec­tive Module
  • Mar­ke­ting Module

This course deals with the manage­ment of acqui­si­tion and new custo­mers as well as with the manage­ment of long-term customer loyalty of pro­fi­table custo­mers from a company’s point of view. All cen­tral topics of customer manage­ment are con­si­dered regar­ding the back­ground of maxi­mi­zing the value of the customer base (“Customer Equity”). Con­se­quently, customer acqui­si­tion, customer reten­tion, and value-based customer migra­tion are at the core of customer manage­ment. The aim of this course is, the­re­fore, to convey the metho­dical con­cepts of customer manage­ment and their app­li­ca­tion to a large number of market-rele­vant pro­blems by lear­ning the necessary skills.

Customer Base Anaylsis

  • Com­pul­sory Elec­tive Module
  • Mar­ke­ting Module

By par­ti­ci­pa­ting in the course, stu­dents acquire a “toolbox” of sto­chastic models for customer eva­lua­tion, which are increa­singly used in com­pa­nies with com­pre­hen­sive customer data­bases, such as mail-order com­pa­nies. In addi­tion, we teach mathe­ma­tical basics as well as mar­ke­ting-theo­re­tical basics of tran­sac­tion beha­vior, which enable stu­dents to create their own sto­chastic models. Stu­dents acquire the theo­re­tical foun­da­tions of quan­ti­ta­tive models in mar­ke­ting and the abi­lity to cri­ti­cally reflect on quan­ti­ta­tive models and apply them to prac­tical issues such as customer eva­lua­tion. Thus, stu­dents learn not only the theo­re­tical basis of sto­chastic models but also their app­li­ca­tion to real data in order to per­form customer eva­lua­tions.

Marketing Seminar

  • Com­pul­sory Elec­tive Module
  • Mar­ke­ting Module
The aim of this module is to learn and apply methods of sci­en­tific work in the con­text of a seminar paper. Course par­ti­ci­pants are able to pre­pare, ana­lyze and dis­cuss the sci­en­tific lite­ra­ture regar­ding a spe­cific, rese­arch-rele­vant topic (a seminar paper of 15 pages). They can pre­sent the cen­tral fin­dings of the lite­ra­ture as well as its clas­si­fi­ca­tion in two pre­sen­ta­tions.

Empirical Management Research

  • Com­pul­sory Elec­tive Module
  • Mar­ke­ting Module

In the course “Empi­rical Manage­ment Rese­arch”, stu­dents acquire app­li­ca­tion-ori­ented spe­cia­list know­ledge about rele­vant survey methods (e.g. ques­ti­onn­aire design) and ana­lysis methods (e.g. regres­sion ana­lysis) in the field of social sci­ences. They under­stand how mana­gers can apply these methods to busi­ness decision situa­tions. Upon com­ple­tion of the course, stu­dents will have the abi­lity to deter­mine the appro­priate pro­ce­dure for a prac­tical pro­blem, to per­form it cor­rectly, and to inter­pret the results logi­cally to solve the pro­blem. The accom­panying exer­cise should make a signi­fi­cant con­tri­bu­tion to the deve­lop­ment of this metho­do­lo­gical com­pe­tence. The par­ti­ci­pants develop the abi­lity to transfer the know­ledge gained in the lec­ture to con­crete ques­tions. The stu­dents are able to apply the ana­lysis methods accord­ingly and to eva­luate them using the SPSS sta­tis­tics soft­ware. After com­ple­ting the course, stu­dents will have metho­do­lo­gical com­pe­tence in the field of social sci­ences, both on a theo­re­tical and on an app­li­ca­tion-ori­ented level.

Digitalisation and Information Systems Modules

Here you can find all cur­r­ently offered courses in the field of Infor­ma­tion Manage­ment.

Digital Business Models and Technologies

  • Com­pul­sory Elec­tive Modules
  • Digi­ta­li­sa­tion and Infor­ma­tion Sys­tems Module

The course con­veys theo­re­tical and prac­tical con­cepts of how today’s infor­ma­tion sys­tems and tech­no­lo­gies, tog­e­ther with advanced algo­rithms and data ana­lysis, enable new, dis­rup­tive digital busi­ness models and sys­tems. In case stu­dies and the deve­lop­ment and ana­lysis of soft­ware com­pon­ents of digital busi­ness models, stu­dents will develop digital busi­ness models, eva­luate them cri­ti­cally and from various per­spec­tives, assess the requi­re­ments of infor­ma­tion sys­tems, and plan and imple­ment digital trans­for­ma­tions in a reflec­tive manner. Stu­dents develop their own digital busi­ness models in teams and pre­sent them at dif­fe­rent stages during the course.

Customer Relationship Management

  • Com­pul­sory Elec­tive Module
  • Digi­ta­li­sa­tion and Infor­ma­tion Sys­tems Module

Stu­dents of this module receive com­pe­tences regar­ding the inde­pen­dent plan­ning and pro­ces­sing of com­pre­hen­sive tasks within the scope of CRM. The sub­areas of ope­ra­tive and ana­ly­tical CRM are dealt with in detail as well as the course of the entire CRM pro­cess.

Finance Modules

Here you will find all the courses cur­r­ently offered in the field of finance.

Seminar Finance and Banking

  • Com­pul­sory Elec­tive Module
  • Finance Module

In this module, stu­dents pre­pare a seminar paper on a cur­rent rese­arch topic and pre­sent it after­wards. By working on a cur­rent rese­arch topic, stu­dents gain deeper insights into cur­rent prac­tical and theo­re­tical ques­tions of finan­cing and ban­king manage­ment. Through the exchange with their fellow stu­dents and by defen­ding their work, stu­dents also learn to pre­sent their own fin­dings, to cri­ti­cally appre­ciate them and to defend them argu­men­ta­tively. One of the aims of the course is to pre­pare stu­dents for the pre­pa­ra­tion of their master thesis.

Research Project Finance and Banking

  • Com­pul­sory Elec­tive Module
  • Finance Module

In this module, stu­dents con­duct empi­rical rese­arch at a high sci­en­tific level. From the respec­tive for­mu­la­tion of the rese­arch ques­tion to the ela­bo­ra­tion of an empi­rical model and its pro­gramming in sta­tis­tical soft­ware to the inter­pre­ta­tion of the results, all essen­tial steps of empi­rical sci­en­tific work are car­ried out inde­pendently. The­re­fore, an advanced level of know­ledge regar­ding the app­li­ca­tion of eco­no­metric methods is required. One of the aims of the course is to pre­pare stu­dents for the pre­pa­ra­tion of a later master thesis.

Credit Risk Modeling

  • Com­pul­sory Elec­tive Module
  • Finance Module

In this course, stu­dents will learn various methods for mode­ling credit risks (e.g. option price theory, asset value model, risk-neu­tral default pro­ba­bi­li­ties) at the indi­vi­dual and port­folio level. After com­ple­ting the course, stu­dents will be able to link these methods to real pro­blems and apply them inde­pendently with the help of Excel VBA. Stu­dents also learn to assess and clas­sify the results of a risk ana­lysis.

Empirical Finance

  • Com­pul­sory Elec­tive Module
  • Finance Module
The course gives stu­dents an over­view of common eco­no­metric methods, espe­ci­ally in the field of regres­sion ana­lysis. Stu­dents learn the pre­re­qui­sites, advan­tages, and dis­ad­van­tages of dif­fe­rent methods and apply them inde­pendently in cor­re­spon­ding case stu­dies. The course par­ti­ci­pants also learn how to use the Bloom­berg data­base and the Stata sta­tis­tical soft­ware. The aim of the course is to enable stu­dents to pro­duce sci­en­tific papers with high-qua­lity empi­rical com­pon­ents.

Risk Management

  • Com­pul­sory Elec­tive Module
  • Finance Module

The module deals with the recording and manage­ment of various risk types (e.g. for­eign cur­rency risks, inte­rest rate risks, credit default risks) that occur in finan­cial com­pa­nies. In addi­tion to risk mea­sures and their app­li­ca­tion to ope­ra­tional decision-making pro­blems, super­vi­sory regu­la­tions on risk limi­ta­tion are also dealt with. The aim of the course is to pro­vide stu­dents with know­ledge in the mea­su­rement and con­trol of risks in finan­cial com­pa­nies.

Ethics Modules

Here you will find all the courses cur­r­ently offered on the ethics module.

Advanced Economic Ethics

  • Man­datory Module
  • Ethics Module

This course pro­vides stu­dents with in-depth know­ledge of the theo­ries and methods of wel­fare eco­no­mics and dis­tri­bu­tive jus­tice. The aim of this module is to enable stu­dents to per­ceive and ana­lyze pro­blems of the world eco­nomy and to develop solu­tions.

Social Innovation (SI)

  • Man­datory Module
  • Ethics Module

Stu­dents of this module receive an over­view of inter­di­sci­pli­nary con­cepts of inno­va­tion and social inno­va­tion, social entre­pre­neurship, and cor­po­rate citi­zenship. To this end, stu­dents develop an under­stan­ding of the social pre­re­qui­sites for entre­pre­neu­rial action, with par­ti­cular emphasis on entre­pre­neu­rial inno­va­tion.

Advanced Business Ethics

  • Man­datory Module
  • Ethics Module

In this module, stu­dents are taught basic con­cepts of busi­ness ethics and are cri­ti­cally ques­tioned. Stu­dents learn con­cepts such as cor­po­rate social respon­si­bi­lity, cor­po­rate citi­zenship, and sustai­na­bi­lity. The aim of the course is for stu­dents to develop an under­stan­ding of the over­ar­ching inter­re­la­ti­ons­hips bet­ween dif­fe­rent dimen­sions of respon­sible cor­po­rate actions in the con­text of social deve­lop­ments.

Business Ethics and Statistics

  • Man­datory Module
  • Ethics Module

In this course, cur­rent social issues such as poverty and ine­qua­lity are ana­lyzed and ques­tioned with the help of the R soft­ware envi­ron­ment. The aim of the course is to enable stu­dents to under­stand, ques­tion and deter­mine key figures of busi­ness ethics.

Lecture Series "Sustainability in China"

  • Man­datory Module
  • Ethics Module
This module deals with rele­vant aspects of sustainable deve­lop­ment and sustai­na­bi­lity manage­ment in China. It will pro­vide mul­ti­di­sci­pli­nary insights in areas such as eco­no­mics, engi­nee­ring, entre­pre­neurship, envi­ron­mental sci­ences, and cul­tural geo­graphy. The aim of the course is for stu­dents to develop a better under­stan­ding of the social, poli­tical and cul­tural struc­tures and pro­cesses of the People’s Repu­blic of China and their effects not only in cities but also in rural areas.