Intensive Course C++

Limited number of participants!

Please register by email to, stating your name, student ID number, study program - Studiengang, and semester.

Please do not forget to register with your Prüfungsamt as well.

Registration period: from December 1, 2018 to January 11, 2019.

Please note that contrary to before the course will only take place each winter semester. I.e., there will be no block course in August / September 2019.

The block course provides a short but extensive introduction to the programming language C++. It is aimed at students that have a solid knowledge of Java, Python, or another imperative programming language. C++ is used in many research groups in the "Institut für Neuroinformatik" (Institute for Neural Computation).

  - basics of imerative programming in C / C++
  - basic language constructs
    - arrays, pointer arithmetic, references, dynamic memory management
    - basic classes in C++: string, vector
  - classes and object orientation in C++
    - const-correctness
  - inheritance, polymorphism
    - further class concepts: static member, rule of three (five)
  - templates
    - metaprogramming
  - standard library
  - miscellaneous (mostly C++14 / C++17)
     - move semantics, exceptions, auto-declare, initializer syntax, casting, enumerations
  - multi-threading (later than C++11)
     - also smart pointers



Course type
Lab courses
4 CP
Winter Term 2018/2019


Lab course
Takes place every day from 09:00 to 17:00 in room CIP Pool (1) ID 03/139.
First appointment is on 18.02.2019
Last appointment is on 01.03.2019


It is assumed that participants are already familiar with an imperative, possibly object oriented programming language, e.g., Java. This course is not suited for programming beginners.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210