Computer Science (Bachelor of Arts, B.A.)
In the Teacher training programme in Computer Science at Humboldt-Universit?t, you will acquire sound subject-matter and didactic knowledge, set individual priorities with diverse specialization options, and optimally prepare yourself for teaching.
Table of Contents
At a glance
Course structure and content
You will learn the fundamentals of programming, algorithms and data structures, as well as theoretical computer science and digital systems. You will explore the abstraction of complex problems and develop solutions relevant to a wide range of applications. Additionally, you will gain insights into database systems, software engineering, and modern technologies. The didactic component prepares you to teach computer science in an understandable and motivating way. Furthermore, you will acquire skills in educational technologies, language teaching, and educational science.
Mandatory Modules (57 CP)
| Module | Title | Size |
|---|---|---|
| SQ | Computer Science Key Qualifications | 5 CP |
| B1 | Programming Fundamentals | 12 CP |
| A2 | Algorithms and Data Structures | 9 CP |
| A1 | Introduction to Theoretical Computer Science | 9 CP |
| C2K | Digital Systems for Computer Science Teacher Training | 7 CP |
| W3K | Fundamentals of Database Systems | 5 CP |
| FD | Introduction to the Didactics of Computer Science | 5 CP |
| BT | Educational Technologies | 5 CP |
Mandatory Elective Modules (10 CP)
Modules of free choice totaling 10 CP out of the following must be completed:
| Module | Title | Size |
|---|---|---|
| S | Seminar | 5 CP |
| W5-n | Special Topics in Computer Science 5-n (n= 1,2,3...) | 5 CP |
| W10-n | Special Topics in Computer Science 10-n (n= 1,2,3...) | 10 CP |
It is also possible to choose other Mandatory Elective Modules or the Mandatory Module M1K from the main field of study in Computer Science. However, this means that in this case, more than the prescribed 10 ECTS credits will be completed in the elective area.
Special features
The program is characterized by a strong connection between theoretical foundations and practical application. From the very first semester, you will acquire scientific fundamentals that are systematically developed and deepened. We place great emphasis on equipping you with conceptual and methodological skills that go beyond short-term trends.
Furthermore, you will benefit from a modern study infrastructure with new buildings, state-of-the-art technology, and an attractive campus in Adlershof.
The low exam workload and the opportunity to choose your own specialization create optimal conditions for your studies.
For this course of study, you should enjoy logical and abstract thinking and have an interest in mathematical and technical issues. Equally important are communication skills and a desire to share knowledge, as you will be preparing for a teaching career.
Creativity and problem-solving skills will help you understand and explain complex topics. Teamwork and initiative will also support you throughout your studies.
Subject-specific admission and enrolment rules
Career opportunities & prospects
If you are aiming for a teaching career, apply for the Master of Education (M.Ed.) programme in your two subjects. Alternatively, you could apply for a Master's degree in Statistics at Humboldt-Universit?t, for example.
Find out more in the course catalogue or via the database Hochschulkompass nationwide.
With a combined Bachelor's degree in Computer Science, you can apply for a Master of Education to work as a computer science teacher in schools. Alternatively, other Master's programmes are available, for example in Statistics or related fields. Furthermore, you will have diverse opportunities in education, software development, or research.
More information on career prospects and alternatives can be found in the Berufenet database.
Course Advisory Service
Prof. Dr. sc. nat. Verena Hafner
Recognition of credits
Examination Office, Ms. Feise-Nasr, phone: 030/2093 81135, pruefungsbuero.informatik.master@hu-berlin.de
Contact information for the institute
Department of Computer Science
Johann von Neumann-Haus, Institutsgeb?ude, Rudower Chaussee 25, 12489 Berlin