Course of Study International Management and Engineering (Study Cohort w17)

Sample course plan D  Master International Management and Engineering (IWIMS)
Specialisation II. Information Technology
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Core qualification CompulsorySpecialisation CompulsoryFocus CompulsoryThesis Compulsory
Core qualification Elective CompulsorySpecialisation Elective CompulsoryFocus Elective CompulsoryInterdisciplinary complement
LP
Semester 1FormHrs/wk
Semester 2FormHrs/wk
Semester 3FormHrs/wk
Semester 4FormHrs/wk
1
Quantitative Methods - Statistics and Operations Research
Quantitative Methods - Statistics and Operations ResearchVL3
Quantitative Methods - Statistics and Operations Research2
Economics
Main Theoretical and Political ConceptsVL2
International EconomicsVL2
Project Seminar IWI
Project Seminar IWIPS3
Master Thesis
2
3
4
5
6
7
Institutional Environment of International Management
Business Environment of Selected CountriesSE3
Research Methods in International ManagementSE1
Organization international companies and IT
Logistics and Information TechnologyVL2
Human Resource Management and Organization DesignVL2
Organization and Process ManagementPBL2
Strategic Management
Strategic ManagementVL4
8
9
10
11
12
13
Accounting
Corporate FinanceVL2
Management and Financial AccountingVL4
Marketing (Sales and Services / Innovation Marketing)
Marketing PBL5
Corporate Entrepreneurship & Growth
Corporate Entrepreneurship in the Digital AgeSE3
Entrepreneurial FinanceSE2
14
15
16
17
18
19
International Business
International ManagementVL2
Business-to-Business MarketingVL2
Intercultural Management and CommunicationVL2
Technology Entrepreneuship
EntrepreneurshipVL2
Creation of Business OpportunitiesPBL3
Intelligent Autonomous Agents and Cognitive Robotics
Intelligent Autonomous Agents and Cognitive RoboticsVL2
Intelligent Autonomous Agents and Cognitive RoboticsUE2
20
21
22
23
24
25
Production and Logistics Management
Strategic Production and Logistics ManagementPBL3
Operative Production and Logistics ManagementVL2
Machine Learning and Data Mining
Machine Learning and Data MiningVL2
Machine Learning and Data MiningUE2
26
27
28
29
30
Nontechnical Elective Complementary Courses for Master (from catalogue) - 6LP

The choice of courses from the catalogue is flexible (depends on the semestral work load), provided the necessary number of required credits is reached.