Hochschule KarlsruheHochschule Karlsruhe - University of Applied Sciences
Hochschule KarlsruheHochschule Karlsruhe - University of Applied Sciences
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Data Science (B.Sc.)

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Structure of the program

The standard period of study for the Bachelor in Data Science is seven semesters. The study program is divided into two semesters of basic studies and 5 semesters of advanced studies. An internship is scheduled in the fifth semester.

The program provides a comprehensive education in all major Data Science fields, covering both theory and practice. The necessary technical and interdisciplinary skills are taught through a balanced mix of courses from the fields of computer science, economics, mathematics and statistics.

Your studies are completed by the practice-oriented application of the course content in the form of Data Science projects, internship semester and domain projects.


Miriam Semling
Nicole Bregulla

Phone: +49 (0)721 925-2966
sekretariat.wi.iwispam prevention@h-ka.de

Office hours:
Mo.–Do. 08:00–13:00 Uhr
Fr. 08:00–12:00 Uhr

Geb. E, Raum 109
Moltkestraße 30
76133 Karlsruhe

A balanced mix of courses from the fields:

Computer science

In the computer science modules you will learn the basics of programming and data management - to a depth that is needed in typical data science projects.

After completing the compulsory program of your advanced studies, you will know the most important basic principles of machine-learning systems and will be able to carry out data analytics projects independently as well as to work with common Big Data architectures.

The electives and domain projects in the 6th and 7th semesters allow you to specialize and thus, for example, to deepen computer science basics in order to be able to follow a computer science master's degree, or to gain more experience in machine learning.


After the introductory module in the 1st semester, you will carry out a Data Science project in each of the 2nd to 4th semesters, during which the basic economic knowledge required for this is taught. Subjects from the areas of computer science, statistics and mathematics also pick up on this project and illustrate the respective course content using this application example.

You will spend the 5th semester as internship semester in a company, where you will usually independently carry out a Data Science project on a problem from the field of economics.

In the domain projects and electives of the 6th and 7th semesters,  you will deepen your basic knowledge in the field of economics and further expand knowledge in application domains of your choice.


In the statistics modules you will learn the theoretical foundations of data analysis and develop an understanding of how reliable your conclusions drawn from data are.

You will then use application examples to develop systematic approaches to typical data analytics problems. Machine learning also uses many of the concepts covered in statistics.


In the mathematics modules, you will learn the fundamentals of calculus, linear algebra, and logic, which are used in the economics, statistics, and machine learning and data analytics modules.

In addition, there is an emphasis on mathematical modeling, which is the ability to put real-world issues, problems, and data into a form to which the theoretical methods you learn can be applied.

Module descriptions

The module handbook provides a detailed description of the individual course contents covered during the seven semesters.

First semester - basic studies
Fundamentals of Analysis
Descriptive Statistics
Computer Science for Data Science 1
Databases and Data Science 1
Economic Fundamentals for Data Science

Second semester - basic studies

Basics Linear Algebra
Computer Science for Data Science 2
Databases and Data Science 2
Target and Key Figure Oriented Control
Third semester - advanced studies
Data Analysis and Business Intelligence 1
Data Mining & Machine Learning Basics 1
Data Engineering
Project Management & IT Projects
Analysis of Market and Customer Data
Fourth semester - advanced studies
Optimization Methods, Modeling and Simulation
Data Analysis and Business Intelligence 2
Data Mining & Machine Learning Basics 2
Data protection & Ethics
Analysis of Process and Product Data
Fifth semester - advanced studies
Internship Preparation
Internship Semester

Internship Follow-up




Sixth semester - advanced studies
Compulsory Elective 1
Compulsory Elective 2

Domain Project 1




Seventh semester - advanced studies
Domain Project 2
Bachelor Seminar
Bachelor’s Thesis


The courses are taught in German language, individual lectures are held in English as language of instruction. At the university's own Foreign Language Institute all students can deepen their own language skills in lessons with native speakers. 

Foreign Language Institute

Internship & studying abroad Career prospects Organization & exams