Information Management
Information management is one of the central activities in modern knowledge-driven societies. As the amount and variety of data increase at an unprecedented rate, access to relevant, structured, and unstructured data poses significant challenges. This theme provides you with a deep understanding of scientific and practical aspects of information management and the skills to design, develop, and evaluate information systems from both technological and human perspectives.
Year 1 |
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Quarter 1 |
Quarter 2 |
Quarter 3 |
Quarter 4 |
| Software Architecture | Core course | Responsible Computer Science | Research course |
| Core course | Theme 1 | Theme 1 | Theme 1 |
| Core course | Theme 2 | Theme 2 | Theme 2 |
Credits: each course in a theme is 5EC, so each theme is 15EC.
Students choose 2 themes, each of which has 3 courses in the 2nd, 3rd and 4th quarters of the 1st year. For this theme, you will take the following courses:
Q2 - Crowd Computing
The course Crowd Computing delves into a dynamic research field at the nexus of computer science and data science, exploring how large groups of people can collectively tackle complex tasks beyond the reach of artificial intelligence alone. Through algorithmic engagement on web-enabled platforms, students examine the creation, enrichment, and interpretation of data, integral to data science applications. With a focus on scientific and technical foundations, the course investigates crowd computing's role in computer science applications such as information retrieval and machine learning, as well as its real-world impact in areas like cultural heritage preservation and smart cities development.
Q3 - Information Retrieval
Information Retrieval is the discipline that deals with the representation, storage, organisation of, and access to information items, and it is concerned with providing efficient access to large amounts of unstructured contents, such as text, images, videos etc. The objective of this course is to introduce the scientific underpinnings of Information Retrieval. The course aims at providing you with basic information retrieval concepts and more advanced techniques for efficient data processing, storage, and querying. Covered topics include: information retrieval models, indexing techniques, web search, evaluation of information retrieval systems, and recommender systems.
Q4 - Web Science & Engineering
The main subject of this course is the web, and in particular web data. It considers developments in the web and the (big) data management challenges associated to it. In particular, the course considers the relationships between people and technology that come with the web and web-based information systems, both from an engineering perspective as well as from an analytical perspective. The course explains the concept of web-based information system and thus concentrates on a large class of modern information systems that use the web and web data in one way or another. It also considers research in social web data analytics and data science techniques to extract user knowledge from social web data.