Intensive Course C++

Course is full! Further registrations will be put on a waiting list for WS16/17 Please register by email to stating your name, student ID number, study program (Studiengang), and semester. Enrollment starts on July 25, 2016.

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 or another imperative programming language. C++ is used in many research groups at Institut für Neuroinformatik (Institute for Neural Computation) and is required for the exercises in "Artificial Neural Networks" and "Vision in Man and Machine".

- Basic concept (C/C++): control structures, type system, operations, implicit/explicit casts, functions, declarations/definitions, preprocessor, pointer and arrays, internal/external bindings, compiler-linker-concept, memory management

- Classes in C++: references, const-qualifier, default-parameter, encapsulation, abstraction, polymorphy, constructor/destructor, overloaded functions, copy-constructor, assignment operator, inheritance, virtual functions, abstract classes/interfaces, static/dynamic binding, static elements/methods

- Templates: template functions, template methods, template classes, inline, explicit inline, specialization, meta programming

- Standard Template Library (STL): cout, cin, string, fstream, vector, list, queue

- Parallelization in C++ 11



Course type
Lab courses
4 CP
Summer Term 2016


Lab course
Takes place every day from 10:00 to 18:00 in room CIP (ID 03/139).
First appointment is on 19.09.2016
Last appointment is on 30.09.2016


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