The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required..

The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required.

The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required.

The course covers the fundamental concepts of computer programming with a focus on systematic algorithmic problem solving. Taught language is C++. No programming experience is required.

The course covers the basic concepts of computer programming.

This course provides the foundations of programming and working with data. Computer Science II particularly stresses code efficiency and provides the basis for understanding, design, and analysis of algorithms and data structures. In terms of working with data, foundations required for understanding experimental data and notation and basic concepts for machine learning are covered.

The courses covers the foundations of design and analysis of algorithms and data structures, including graph theory and graph problems. It also introduces generic and parallel programming.

This course provides the foundations of programming and working with data. Computer Science II particularly stresses code efficiency and provides the basis for understanding, design, and analysis of algorithms and data structures.

The course provides the foundations for the design and analysis of algorithms.Classic problems ranging from sorting up to problems on graphs are used to discuss common data structures, algorithms and algorithm design paradigms.The course also comprises an introduction to parallel and concurrent programming and the programming model of C++ is discussed in some depth.

The course provides the foundations for the design and analysis of algorithms.Classic problems ranging from sorting up to problems on graphs are used to discuss common data structures, algorithms and algorithm design paradigms.The course also comprises an introduction to parallel and concurrent programming and the programming model of C++ is discussed in some depth.

The programming model of C++ is discussed in some depth. In particular the mechanisms for efficient memory management and generic programming with C++ are covered.

The topic of this course are operating systems, with an emphasis on concepts. In particular, the course will treat in detail the two main tasks of modern operating systems: resource management and runtime support for programs. Some keywords are: boot process, file systems, memory allocation and garbage collection, processes and threads, device drivers, runtime type support, virtual systems.

The course provides an overview of techniques to build correct software, with a strong focus on testing and program analysis.

This course introduces both theoretical and practical aspects of software engineering, all of which are applied in a substantial team project.

This course introduces both theoretical and applied aspects of software engineering. It covers:- Software Architecture- Informal and formal Modeling- Design Patterns- Software Engineering Principles- Code Refactoring- Program Testing

This is an introduction to probability, statistics, and machine learning for students of mechanical engineering. We cover the fundamental concepts from probability theory, statistics and machine learning, with a focus on applications for mechanical engineering.