Computer Science

This course examines the fundamental techniques of some significant approaches within Artificial Intelligence (AI) for the solution of difficult problems. In particular, the course discusses local research techniques in a space of solutions, systems with constraints, soft constraints, planning techniques, representation and manipulation of knowledge with and without uncertainty, decision theory, reasoning techniques with preferences, and aggregation of preferences in a multi-agent context. The structure and the topics of the course is as follows: problem resolution, and local search algorithms; constraint-based systems and soft constraints; preference reasoning and preference aggregation in multi-agent systems; decision theory; treatment of uncertainty and probabilistic reasoning; planning; and artificial intelligence in society. The course recommends students have basic knowledge of programming and algorithms as a prerequisite.

This course examines the principles, mathematical models and applications of computer vision. Topics include: image processing techniques, feature extraction techniques, imaging models and camera calibration techniques, stereo vision, and motion analysis.

This course explores both theoretical and practical aspects of cryptography, authentication, and information security. Students learn the relevant mathematical techniques associated with cryptography, the principles of cryptographic techniques and how to perform implementations of selected algorithms in this area, and explore the application of security techniques in solving real-life security problems in practical systems.

This course provides the practical tools for developing, applying, and investigating machine learning methods in Python. The course utilizes libraries including Pandas, PyTorch, JAX, and Cython.

In this hands-on course, students work in interdisciplinary teams to uncover the rich history of Utrecht and share findings with the public. Combining historical, architectural, and societal data, students develop and design an innovative application for the city of Utrecht. In the process, students cooperate across disciplinary borders, take charge of their own learning process, and experimentally assess the added value of new media and ICT. The course accumulates in presentations and interactive demos of the teams’ final prototypes.

This course introduces the digital tools and methods used for research in the Humanities.  The theoretical part of the course focuses on basic concepts that are essential for working with large quantities of humanities data, including corpora and databases, searching techniques, information retrieval, and statistical language models. In the practical part of the course, students learn how to do basic text analysis using the programming language Python.
 

This course provides an introduction to single machine organization, architecture and operation. Upon successful completion of the class, students learn how to demonstrably understand how instructions get executed in a sequential processor; be able to perform arithmetic operations in binary and conversions between number systems; be able to compose and analyze small assembly-language programs; explain and illustrate memory concepts and performance improvement measures.