Bachelor Data Science (2025) - Interactive curriculae of TU Ilmenau

The interactive curriculae provide information on the degree programmes offered by the TU Ilmenau.

Please refer to the respective study and examination rules and regulations for the legally binding curricula (Annex Curriculum).

You can find all details on planned lectures and classes in the course catalogue.

Please note that this page is no longer updated. All modules and study plans from PO version 2021 onwards (Bachelor and Master study programs) are now available on the Campus Portal.

This curriculum is planned for 6 semesters and a total of 180 credit points.

	1. Sem			2. Sem			3. Sem			4. Sem			5. Sem			6. Sem			exam	CP
module	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	exam	CP
Mandatory Section																				125
Lecture Series on Data Science	1	2	0																SL	5
Linear Algebra 1	5	3	0																sPL 120 min	10
Mathematics for Computer Scientists 1	4	2	0																sPL 90 min	5
Programming and Algorithms	3	2	0																sPL 90 min	5
Algorithms and Data Structures 1				2	2	1													PL	5
Applied Probability Theory and Mathematical Statistics				2	2	0													aPL	5
Linear Algebra 2				5	3	0													mPL 30 min	10
Mathematics of Data Science				2	2	0													sPL 120 min	5
Advanced Mathematics of Data Science							2	2	0										sPL 120 min	5
Algorithms and Data Structures 2							2	2	0										sPL 90 min	5
Database Systems							2	1	1										PL	5
Graphs & Algorithms							2	1	0										sPL 60 min	5
Machine Learning							2	2	0										PL	5
Probability Theory and Mathematical Statistics							2	2	0										mPL 30 min	5
Software Development							2	1	0	1	1	0							PL	10
Data Management and Data Analysis										2	2	0							sPL 90 min	5
Numerics										3	1	0							mPL 30 min	5
Optmization										4	2	0							mPL 30 min	10
Deep Learning													2	2	0				PL	5
Ethics for Data Science													0	2	0				PL	5
Bachelor Seminar Data Science										150 h									SL	5
	1. Sem			2. Sem			3. Sem			4. Sem			5. Sem			6. Sem			exam	CP
module	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	exam	CP
Wahlbereich Data Science																				10
Multivariate Statistics 1										2	1	0							mPL 30 min	5
Time Series Analysis										2	1	0							mPL 30 min	5
Computer Graphics													2	2	0				aPL	5
Modelreduction													2	1	0				mPL 30 min	5
Data-Driven Optimization for Machine Learning Applications																2	2	0	PL	5
Wahlbereich Informatik																				10
Database Systems Architectures										2	2	0							PL	5
Distributed Systems										3	1	0							mPL 30 min	5
Programming Paradigms										3	2	0							sPL 90 min	5
Logic and Logic Programming													3	2	0				sPL 150 min	5
Software Engineering 2																2	1	0	mPL 30 min	5
Wahlbereich Mathematik																				10
Game Theory										2	1	0							mPL 30 min	5
Large Networks & Random Graphs										2	1	0							mPL 30 min	5
Global Optimization													4	2	0				mPL 30 min	10
Stochastic Processes													4	2	0				mPL 30 min	10
Vector Optimization													4	2	0				mPL 30 min	10
Numerics 2																2	1	0	mPL 30 min	5
	1. Sem			2. Sem			3. Sem			4. Sem			5. Sem			6. Sem			exam	CP
module	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	L	E	P	exam	CP
Ergänzung (Kurs o. Modul aus dem Lehrangebot der Universität)																				5
Softskills																				5
English for Special Purposes - Data Science				0	3	0													SL	3
Spracherwerb (aus englischsprachigem Lehrangebot des Zentralinstituts für für Bildung)																				2
Final Thesis																				15
Bachelor´s Thesis with Colloquium																450 h			PL	15

Legend

Kind of examination
Sem	semester
L	lecture
E	exercise course
P	practical exercise
CP	credit points
PL	examination performance
SL	pass-fail certificate (Grading according to curriculum)
BA	bachelor thesis
MA	master thesis
DA	diploma thesis
Form of examination
a	alternative
e	electronic
k	Kolloquium
m	oral
p	practical examination with pass/fail certificate
s	written
MC	multiple choice