Master of Science in Cognitive Computing and Collective Intelligence
University of Jyväskylä
Jyväskylän yliopisto, Finland
EUR 8,000 / per year
17 Jan 2024
Earliest start date
Master’s Degree Programme in Artificial Intelligence provided by the Faculty of Information Technology is a two-year (120 ECTS) full-time programme taught in English. In our programme, we provide a wide view on the AI domain including modern and advanced (and remarkably interesting) topics of it (with appropriate models, algorithms, and tools) such as:
- machine learning, deep learning, and cognitive computing;
- knowledge representation, reasoning, and decision-making;
- semantic web, linked data, and knowledge graphs;
- artificial general intelligence, autonomous agents, and collective intelligence;
- AI & security (AI as subject, object or instrument of attack and defence).
In our courses, you will learn how to professionally use Artificial Intelligence (i.e., already developed models, algorithms, and tools) in your everyday business to solve complex problems or/and how to design and develop new and better artificial intelligence (i.e., new models, algorithms, and tools).
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.
On completion of the programme, our 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.
Possible career paths for graduates of the MSc Cognitive Computing and Collective Intelligence are manifold from Cloud Service Architects to Researchers.
- Software (Cloud) Service Architects: designing the technical infrastructures of service enabled applications;
- Enterprise Architects: architecting and aligning enterprises processes, structure, data and control;
- Web Service (IT) Professionals: experts in the development and composition of Web services into enterprise applications;
- Big Data and Knowledge Engineers, Architects, Modellers and Analysts: experts in Big Data, metadata and ontology engineering, knowledge management, data and knowledge integration and evolution, in constructing data-as-a-service solutions, data-intensive applications, expert-systems and knowledge based-systems;
- Analytics Professionals: experts in decision making and support, optimization based decision making, prescriptive analytics;
- Researchers (PhD studies): graduates are well-prepared to successfully pursue a career in academia.