Start of Studies at the Institute of Computer Science

Here you will find information, guidance, and tips for starting your studies in Computer Science. This includes everything from questions about beginning your studies in the summer semester, finding accommodation and financing options, required prior knowledge, and planning your timetable for the first semester, to study organisation, exam regulations, and even non-subject-specific services offered by the University of Augsburg.

 


 

Studying in Augsburg

Studying in the city of the Fuggers, water, and the famous "Puppenkiste Kasper" – Augsburg is neither too big nor too small, making it a great place to be a student. But where should you live? How can you finance your studies? And what does the city have to offer beyond university life?

 

The University of Augsburg and the Student Services (Studentenwerk) provide support and advice on finding accommodation and financing your studies.

 

Important Information before Starting your Studies

  1. Early Enrollment to receive your IT identifier (RZ-Kennung). (Bachelor & Master)

  2. Access the learning platform Digicampus with your RZ-Kennung. (Bachelor & Master)
  3. Set up Wi-Fi and email access – you should always be reachable via your student email. (Bachelor & Master)

  4. Register for preparatory, adjustment, and bridging courses. (Bachelor)

  5.   Note deadlines and plan your personal schedule. (Bachelor & Master)
  6. Attend welcome events for first-semester students (Bachelor & Master).  

 

 

 

 

We warmly welcome you to the start of the summer semester 2025 with the following introductory events for Computer Science as a major, minor, or subsidiary subject:

 

Bachelor

 

We generally offer multiple alternative welcome sessions, both in person and online, for Bachelor’s students in Computer Science. These take place before the first week of lectures, starting from 31st March. You should not miss these sessions. Access to the welcome sessions is provided via our teaching platform, Digicampus. To log in, you will need your RZ credentials, which you will receive after enrolment.

We also provide information slides and screencasts to help you get started with your studies. These can be downloaded below and should be viewed in advance.

Additionally, several preparatory and bridging courses take place before lectures begin. Besides the Preparatory Course in Computer Science (winter semester) / Adjustment Course in Java (summer semester), you should also register in time for the Mathematics Bridging Course that suits your needs.

The first week of lectures will begin with the first session of "Computer Science 2" on Thursday, 24th April, from 10:00 - 11:30, in Lecture Hall 1 of the Lecture Hall Centre (Building C).

 

Access to the Bachelor's Welcome Event (Digicampus)

 

Master

 

We offer an in-person welcome session for Master’s students in Computer Science. This is particularly useful for those who are new to Augsburg. Access to the welcome session is provided via our Digicampus teaching platform. To register, you will need your RZ-Kennung (IT identifier), which you receive after enrolment.

 

Access to the Master's Welcome Event (Digicampus)

 

Overview of All Introductory Events

  1. General Bachelor’s Welcome

    • Monday, 31st March 2025, 10:00 - 11:30 (Room 2045 N): Introduction to the Java Adjustment Course and Q&A session on starting your Computer Science studies.
    • Monday, 7th April 2025, 10:00 - 11:30 (Online): General welcome and Q&A session for starting Computer Science. 
  2. Specific Bachelor’s Programmes
    • TBA
  3. General Master’s Welcome
    • Friday, 11th April 2025, 10:00 - 11:30 (Room 2045 N): Welcome and Q&A session for all new students in Augsburg.
 

  

Basic imperative programming skills and mathematical knowledge are required for studying Computer Science as a major, minor, or subsidiary subject at the University of Augsburg. These foundational skills are taught in the following courses:

  • "Preparatory Course in Computer Science" (Winter Semester):

    • Covers basic imperative programming in C.
    • Required for the "Informatik 1" lecture.
    • Intended for Bachelor’s students in Computer Science, Business Informatics, Geoinformatics, Engineering Informatics, Medical Informatics, Data Science, Mathematics & Computer Science, and related programmes.
  • "Adjustment Course in Java" (Summer Semester):

    • Covers basic imperative programming in Java.
    • Required for the "Informatik 2" lecture.
    • Suitable for the same programmes as the winter course.
  • Mathematics Bridging Course (Advanced, every semester):

    • Designed for students in Mathematics-related programmes (e.g. Mathematics & Computer Science, Data Science, etc.).
  • Mathematics Bridging Course (Standard, every semester):

    • Designed for students in Computer Science (except those with a Mathematics minor), Geoinformatics, Engineering Informatics, and Medical Informatics.
  • Mathematics Preparatory Course for Business Informatics (Winter Semester):

    • Exclusively for Business Informatics students.

 

Steps to Take Before Your Course Starts

  1. Enrol to receive your RZ credentials.

  2. Register for your course on Digicampus using your RZ credentials.

  3. Install the necessary software in advance (for programming courses) – support is available if needed.

Der Zugang zur Veranstaltung im Digicampus, dem Studienverwaltungssystem der Universität Augsburg, ist nur mit RZ-Kennung möglich. Damit Du rechtzeitig Zugang zum Digicampus bekommst, empfehlen wir dringend, dass Du Dich so früh wie möglich bei der Studentenkanzlei für Dein Studium einschreibst.


  • Begrüßung in Präsenz: 31.3.2025, 10:00 - 11:30 Uhr, Raum 2045 N
  • Betreuung in Präsenz: 31.3. - 4.4.2025, 12:15 - 15:30 Uhr, Raum 1002 N + 1005 N
  • Anmeldung mit RZ-Kennung: im Digicampus

Themen

  1. Thema 1: Installation und Benutzung der benötigen Software (Java 21, API, Eclipse) / Erstes Programm, Ausgabe auf Kommandozeile und Zeichenketten / Variablen und Konstanten vom Typ double, Wertzuweisungen und Rechenausdrücke / Einblick in die Java-API: Konstanten der Klasse Double
  2. Thema 2: Fallunterscheidungen (if-else) und logische Ausdrücke / Variablen und Konstanten vom Typ boolean / Einblick in die Java-API: Methoden der Klasse Math
  3. Thema 3: Fallunterscheidungen (?:-Operator) / Wiederholungen (while / for) / Variablen und Konstanten vom Typ int / Einblick in die Java-API: Konstanten der Klasse Integer
  4. Thema 4: Methoden / Variablen und Konstanten vom Typ char / Unicode / Einblick in die Java-API: Methoden der Klasse Character
  5. Thema 5: Arrays / Variablen vom Typ String und die Klasse String / Kommandozeilenparameter / Einblick in die Java-API: Konstruktoren und Methoden der Klasse String

Organisation

Zu jedem der 5 Themen wird vorab ein Übungsblatt mit kurzem Überblick über das Thema, Beispielen für den Einstieg, Hinweisen zur Eigenrecherche und Übungsaufgaben im Umfang von ca. 4 - 5 Stunden Bearbeitungszeit herausgegeben (Download siehe unten). 

  • Der Kurs ist primär für die Durchführung im Selbststudium konzipiert. 
  • Bei Fragen stehen Betreuungszeiten in Präsenz zur Verfügung. 
  • Alle Programmieraufgaben können im eigenen Tempo, mit Betreuung (vor Ort) oder ohne Betreuung (zu Hause) bearbeitet werden. 
  • Zu Hause benötigst man einen eigenen PC oder Laptop. 
  • In der Universität stehen Rechner in den Rechnerräumen in begrenzter Anzahl zur Verfügung und es gibt freie Arbeitsplätze, an denen man seinen eigenen Laptop benutzen kann.
  • Es gibt keine Bindung der Themen an die Betreuungstage. 
  • Es besteht die Möglichkeit, auch noch später in der Kurs einzusteigen. 
  • Es wird keine Vorlesung angeboten und es werden keine Musterlösungen zur Verfügung gestellt.

Kombination mit anderen Vorkursen / Brückenkursen

Die Brückenkurse in Mathematik finden 7.4. - 11.4. statt. Wir empfehlen unbedingt die Teilnahme an einem der Brückenkurse. Bitte informiere Dich auf den Seiten der Mathematik über den für deinen Studiengang geeigneten Kurs.

 

Aktuelle Lehrmaterialien zum Selbsstudium

Die Lehrmaterialien bestehen aus 5 Themen, die aufeinander aufbauen. Jedes Thema führt in verschiedene Programmiermethoden ein und bietet dazu Übungsaufgaben an. Man benötigt zur Bearbeitung keine Vorkenntnisse. Programmieren lernt man nur durch üben. Deshalb ist es für den Lernerfolg wesentlich, die Beispielprogramme nachzuprogrammieren und alle Übungsaufgaben zu bearbeiten. Die Arbeitszeit für jedes Thema beträgt ca. 4 - 5 Stunden (Lesezeit + Programmierzeit).

 

  • To create your schedule, register for approximately 30 ECTS credits worth of courses.
  • Check your degree’s examination regulations for required courses.
  • Refer to the course catalogue or sample study plan for recommended courses.
  • Register on Digicampus to receive course updates and access materials.
  • Do not miss your first lecture session, as important details about exercises and exams will be provided.
  • Enrol in an exercise group for each lecture – registration details are given in the first session.

Basic Concepts for Studying

  • Lectures serve as an introduction to major areas of computer science. The lecturer presents various technologies, mathematical models, as well as methods and techniques for their analysis and application.

  • Ideally, attend all scheduled lecture sessions and take your own notes during the lecture.

  • A thorough, independent engagement with the material is essential to fully understand the lectures. To support this, weekly written assignments are given.

  • For each lecture, several small exercise groups of around 20-25 participants are offered. These sessions provide an opportunity to discuss the homework assignments. Group allocation takes place at the beginning of the lecture period.

  • Exercises are a crucial complement to lectures, so you should only attend a lecture if you also actively participate in the corresponding exercises. Expect to spend around 6-8 hours per week per lecture working on the assignments.

  • Form a study group that meets several times a week at the university to work on the assignments together.

Seminars are based on discussion and interaction. Usually, there is a set text or a specific topic for each session. Often, students give presentations or present papers, which are then discussed in class.

 

A seminar usually concludes with a written term paper as the final assessment. In some cases, however, the assessment may also take the form of a presentation or simply attendance. This depends on the specific seminar.

If you encounter difficulties in understanding the material, use the following resources:
 

  • Discuss problems within your study group, your exercise group, and in the Digicampus student forum for the lecture.

  • Read the recommended literature that accompanies the lecture.

  • Visit the Open Study Room.

  • Make use of additional exercise and support sessions, such as global exercises, supervised programming sessions, exam preparation courses, and Q&A sessions.

  • Ask your lecturer or teaching assistants for help—either via email or during/after the lecture.

  • The student representatives can also provide support with academic or organisational questions.

  • If you have questions regarding your individual study plan, personal circumstances, or general difficulties with your studies, the academic advisor for your programme is available to help.

The  open study room serves as a meeting point for learning during the lecture period. All computer science students are welcome to come to Room 1056 in Building N to work on exercises together, discuss lecture topics, and ask questions.

This space is particularly useful for foundational courses such as: Informatik (Computer Sciene) 1-3, Discrete Structures and Logic, Mathematics for Computer Scientists, Introduction to Theoretical Computer Science, Database Systems.

In the STUDIS exam management system, you can find details on exams, submit applications, and register for your exams.

 

 

Contact Persons

Prof. Dr. Matthias Schlesner
Dean of Studies for Computer Science
Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics

Email:

Prof. Dr. Robert Lorenz
Stellvertretender Studiendekan Informatik
Lehrprofessur für nebenläufige Systeme

Email:

Prof. Dr. Peter Michael Fischer
Studienberatung Informatik
Department of Computer Science

Email:

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