Course of Study Data Science (Study Cohort w21)

Sample course plan B Bachelor Data Science (DSBS)
Specialisation Electrical Engineering

Legend:
Core Qualification Compulsory	Specialisation Compulsory	Focus Compulsory	Thesis Compulsory
Core Qualification Elective Compulsory	Specialisation Elective Compulsory	Focus Elective Compulsory	Interdisciplinary complement

Semester 1

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Hrs/wk

Semester 2

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Hrs/wk

Semester 3

Form

Hrs/wk

Semester 4

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Hrs/wk

Semester 5

Form

Hrs/wk

Semester 6

Form

Hrs/wk


Discrete Algebraic Structures
Discrete Algebraic Structures	VL	2
Discrete Algebraic Structures	GÜ	2


Automata Theory and Formal Languages
Automata Theory and Formal Languages	VL	2
Automata Theory and Formal Languages	GÜ	2


Databases
Databases	VL	3
Databases	GÜ	1


Signals and Systems
Signals and Systems	VL	3
Signals and Systems	GÜ	2


Introduction to Information Security
Introduction to Information Security	VL	2
Introduction to Information Security	GÜ	2


Seminars Computer Science
Introductory Seminar Computer Science II	SE	2
Introductory Seminar Computer Science I	SE	2


Procedural Programming for Computer Engineers
Procedural Programming for Computer Engineers	VL	1
Procedular Programming for Computer Engineers	HÜ	1
Procedural Programming for Computer Engineers	PR	2


Stochastics
Stochastics	VL	2
Stochastics	GÜ	2


Numerical Mathematics I
Numerical Mathematics I	VL	2
Numerical Mathematics I	GÜ	2


Foundations of Management
Introduction to Management	VL	3
Management Tutorial	GÜ	2


Data Mining
Data Mining	VL	2
Data Mining	PBL	2


Ethics in Information Technology
Ethics in Information Technology	VL	2
Ethics in Information Technology	SE	2


Mathematics I (EN)
Analysis I	VL	2
Analysis I	HÜ	1
Analysis I	GÜ	1
Linear Algebra I	VL	2
Linear Algebra I	HÜ	1
Linear Algebra I	GÜ	1


Programming Paradigms
Programming Paradigms	VL	2
Programming Paradigms	HÜ	1
Programming Paradigms	PR	2


Algorithms and Data Structures
Algorithms and Data Structures	VL	4
Algorithms and Data Structures	GÜ	1


Graph Theory and Optimization
Graph Theory and Optimization	VL	2
Graph Theory and Optimization	GÜ	2


Machine Learning II
Machine Learning II	VL	2
Machine Learning II	GÜ	2


Enhanced Fundamentals of Materials Science
Materials for Energy Storage and Conversion	VL	2
Enhanced Fundamentals: Ceramics and Polymers	VL	2
Enhanced Fundamentals: Ceramics and Polymers	HÜ	1


Mathematics II (EN)
Analysis II	VL	2
Analysis II	HÜ	1
Analysis II	GÜ	1
Linear Algebra II	VL	2
Linear Algebra II	HÜ	1
Linear Algebra II	GÜ	1


Statistics
Statistics	VL	3
Statistics	GÜ	1


Scientific Programming
Scientific Programming	VL	3
Scientific Programming	GÜ	2


Introduction to Communications and Random Processes
Introduction to Communications and Random Processes	VL	3
Introduction to Communications and Random Processes	HÜ	1
Introduction to Communications and Random Processes	GÜ	1


Bachelor Thesis


Electrical Engineering I: Direct Current Networks and Electromagnetic Fields
Electrical Engineering I: Direct Current Networks and Electromagnetic Fields	VL	3
Electrical Engineering I: Direct Current Networks and Electromagnetic Fields	GÜ	2


Mathematics III (EN)
Analysis III	VL	2
Analysis III	HÜ	1
Analysis III	GÜ	1
Differential Equations 1	VL	2
Differential Equations 1	HÜ	1
Differential Equations 1	GÜ	1


Machine Learning I
Machine Learning I	VL	2
Machine Learning I	GÜ	2


Electrical Engineering II: Alternating Current Networks and Basic Devices
Electrical Engineering II: Alternating Current Networks and Basic Devices	VL	3
Electrical Engineering II: Alternating Current Networks and Basic Devices	GÜ	2

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.