Master's Degree Programme in Cognitive Computing and Collective Intelligence

Degree title:
Master of Science
Degree program type:
Master's Degree
120 cr
Responsible organisation:
Faculty of Information Technology
Coordinating organisation:
Faculty of Information Technology
Curriculum periods:
2020-2021, 2021-2022, 2022-2023


Cognitive Computing (the umbrella label for technologies that ingest data and then learn as their knowledge base grows) simulates human thought processes in a computerized model. It focuses on self-learning and self-managing systems that use artificial intelligence (machine learning, data mining, pattern recognition, natural language processing, etc.) to mimic the way the human brain works. While targeting the automatic decision-making and problem-solving, the Cognitive Computing systems are able to learn their behavior through education. They support forms of expression that are more natural for human interaction, which allows them to interpret data regardless of how it is communicated. The primary value is their expertise and the ability to continuously evolve at enormous scale as they experience new information, scenarios and responses. Cognitive Computing as a technology enables various forms of intelligence interact naturally to collaboratively address complex problems. The technology relies on advances in the study of Collective Intelligence, in regards to not only physical groups of humans, but more to the conceptual and mechanical systems we build. Cognitive Computing and Collective Intelligence is the only way nowadays to address the complexity challenges related to the Big Data and the Internet of Things. Combination of these technologies and challenges is resulting to qualitatively new and efficient Smart Cyber-Physical Systems and Industry 4.0.

Learning outcomes

Students who graduate from the programme will think beyond the routine and will be able not just to adapt to a change but to help to create and control it. This means that our graduates will not be able only to “solve smart problems”, but in addition to it they will be able to “invent new and smart problems” and drive them by “designing artificial smart problem solvers”.

On completion of the programme, graduates will be able to:

* use, design and train complex self-managed and continuously evolving public and private industrial systems, digital ecosystems, cyber-physical systems, systems-of-systems, platforms, services and applications;
* will be able to connect their designs with publicly available Deep Learning and Big Data analytics and Web-based Cognitive Computing capabilities as services;
* will be able to figure-out and approach various challenging aspects of complex problems world-wide, which require collective intelligence and self-managing service-based architectures for their solutions;
* understand, and professionally utilize for that purpose, knowledge on enabling technologies and tools;
* perform research training and academic doctoral level studies;
* will be skillful in international communication due to the integrated language and communication studies.


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