Course of Study Data Science (Study Cohort w21)

Sample course plan C  Bachelor Data Science (DSBS)
Specialisation Electrical Engineering
Legend:
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
Semester 5FormHrs/wk
Semester 6FormHrs/wk
1
Discrete Algebraic Structures
Discrete Algebraic StructuresVL2
Discrete Algebraic StructuresGÜ2
Automata Theory and Formal Languages
Automata Theory and Formal LanguagesVL2
Automata Theory and Formal LanguagesGÜ2
Databases
DatabasesVL3
DatabasesGÜ1
Signals and Systems
Signals and SystemsVL3
Signals and SystemsGÜ2
Introduction to Information Security
Introduction to Information SecurityVL2
Introduction to Information SecurityGÜ2
Seminars Computer Science
Introductory Seminar Computer Science IISE2
Introductory Seminar Computer Science ISE2
2
3
4
5
6
7
Procedural Programming for Computer Engineers
Procedural Programming for Computer EngineersVL1
Procedular Programming for Computer EngineersHÜ1
Procedural Programming for Computer EngineersPR2
Stochastics
StochasticsVL2
StochasticsGÜ2
Numerical Mathematics I
Numerical Mathematics IVL2
Numerical Mathematics IGÜ2
Foundations of Management
Introduction to ManagementVL3
Management TutorialGÜ2
Data Mining
Data MiningVL2
Data MiningPBL2
Ethics in Information Technology
Ethics in Information TechnologyVL2
Ethics in Information TechnologySE2
8
9
10
11
12
13
Mathematics I (EN)
Analysis I VL2
Analysis I HÜ1
Analysis I GÜ1
Linear Algebra I VL2
Linear Algebra I HÜ1
Linear Algebra I GÜ1
Programming Paradigms
Programming ParadigmsVL2
Programming ParadigmsHÜ1
Programming ParadigmsPR2
Algorithms and Data Structures
Algorithms and Data StructuresVL4
Algorithms and Data StructuresGÜ1
Graph Theory and Optimization
Graph Theory and OptimizationVL2
Graph Theory and OptimizationGÜ2
Machine Learning II
Machine Learning IIVL2
Machine Learning IIGÜ2
Introduction into Medical Technology and Systems
Introduction into Medical Technology and SystemsVL2
Introduction into Medical Technology and SystemsPS2
Introduction into Medical Technology and SystemsHÜ1
14
15
16
17
18
19
Mathematics II (EN)
Analysis II VL2
Analysis II HÜ1
Analysis II GÜ1
Linear Algebra II VL2
Linear Algebra II HÜ1
Linear Algebra II GÜ1
Statistics
StatisticsVL3
StatisticsGÜ1
Scientific Programming
Scientific ProgrammingVL3
Scientific ProgrammingGÜ2
Image Processing
Image ProcessingVL2
Image ProcessingGÜ2
Bachelor Thesis
20
21
Electrical Engineering I: Direct Current Networks and Electromagnetic Fields
Electrical Engineering I: Direct Current Networks and Electromagnetic FieldsVL3
Electrical Engineering I: Direct Current Networks and Electromagnetic FieldsGÜ2
22
23
24
25
Mathematics III (EN)
Analysis III VL2
Analysis III HÜ1
Analysis III GÜ1
Differential Equations 1 VL2
Differential Equations 1 HÜ1
Differential Equations 1 GÜ1
Machine Learning I
Machine Learning IVL2
Machine Learning IGÜ2
26
27
Electrical Engineering II: Alternating Current Networks and Basic Devices
Electrical Engineering II: Alternating Current Networks and Basic DevicesVL3
Electrical Engineering II: Alternating Current Networks and Basic DevicesGÜ2
28
29
30
31
32
Non-technical Courses for Bachelors (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.