Media and cognition course: How to cultivate technical leaders in artificial intelligence

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Abstract

Artificial Intelligence technologies has been applied in each aspect of daily work and life and has dramatically changed the landscape of industry. The artificial intelligence and related fields have provided a large number of occupations. How to cultivate leaders and experts in artificial intelligence is one of the important issues in the high-education field. It is very significant for our EECS students to learn the developing histories and the state-of-the-art methods of artificial intelligence, such as Deep Neural Networks and Convolutional Neural Networks. In our Media and Cognition Course, students would be asked to propose and complete their own projects with machine learning and deep learning algorithms in the field of impressive artificial intelligence applications, such as speech recognition, image recognition and natural language processing. And they would have a new perspective that media signal processing/recognition solutions are all originated from the principles of human’s perception/understanding. Both the advanced scientific knowledge and the practical technical expertise are involved in our class to improve students’ performance by enriching their inside knowledge structures. At the end of course, the students showed their original and innovative outcomes, which expressed that they have the abilities to solve specific intelligent tasks in the given time/space structures. Our practice shows that the Media and Cognition Course can increase most of the students’ interest in artificial intelligence. Some of students further researched on how to build smarter decision and prediction methods based on the spatio-temporal information and the cognition of human individuals/groups.

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APA

Yang, Y., & Sun, J. (2018). Media and cognition course: How to cultivate technical leaders in artificial intelligence. In Communications in Computer and Information Science (Vol. 852, pp. 143–149). Springer Verlag. https://doi.org/10.1007/978-3-319-92285-0_21

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