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Netherlands

Master of Science in Artificial Intelligence

Netherlands

Radboud University

Nijmegen, Netherlands

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About Course

Key information
Duration 		: 2 Year
Study Type 		: Full Time
Tuition fees 		: 12645 EUR / 0
Exam Accepted 		: IELTS 6.5/9.0 | TOEFL 90/120
Exam Intake 		: Sep
Conditional Scholarship 		: NA
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Course Description 

  • Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.
  • As humans, we may be intrigued by the complexity of any daily activity. How does it actually work to perceive, learn, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.
  • The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

Specialisation in Intelligent Technology

  • Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
  • The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
  • On the one hand, the Master’s in Cognitive Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.
  • On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.

Specialisation in Cognitive Computing 

  • Developing intelligent machines and new ways for humans and machines to interact, as well as understanding cognition through human behavior.
  • Language and Communication Technology lies at the basis of innumerable innovations in our society and has provided remarkable new services (e.g. social media) and products (e.g. smart phones and tablets). This communication can be in natural language such as Watson, Siri, and Twitter, or understood through a machine learning lens, as in sentiment analysis (e.g., of brands, or emotions), epidemic monitoring, and botnet detection.  But communication is also crucial for personalizing information and making it accessible using other means, such as automatic text summarization, visualizations, and chatbots. Robots are bringing interactions with humans into the physical world, opening channels of nonverbal communication, as well as introducing a host of challenging problems of perception (e.g., object recognition) and action (e.g., navigation).
  • In the Intelligent Technology track of the Master’s degree programme in Artificial Intelligence, we concentrate on these techniques in the broad field of communication and interaction between multiple intelligent agents (be they natural or artificial—and physical, or virtual) with a special focus on language.  We address theoretical problems such as: How language can arise and evolve in communities of intelligent technology? and How can an understanding of language and communication can be used to improve the interactions between intelligent technology?  One particular application area we focus on is how to use artificial intelligence techniques to better understand and improve interactions between agents—be they chatbots, people, or robots.
  • In this specialisation you will learn the psychology of human language and communication and how computers can be used to model and understand this type of interaction data, be it textual, spoken, tweets or clicks.  You will also learn how to process the large amounts of data from interactions that arise on the web, and in robot-human interaction. As most interactions on the web are mediated through apps on smart devices, these courses are complemented by the App-Lab course which teaches you how to set-up, build and evaluate apps to facilitate communication and interaction. You will also learn how to build artificial agents and robots that interact with the physical and social environment. By building such systems you will learn more about how human cognition works.

Entry Requirement

Applicants must have completed a Bachelor’s degree 

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