Deep learning in the IT curriculum

Amy K. Hoover, Adam Spryszynski, Michael Halper

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Deep learning is a form of neural-network based machine learning that is becoming prevalent in many IT endeavors. It is therefore important to expose IT undergraduate students to it somewhere in the curriculum. However, deep learning has mathematical foundations that may be beyond the reach of the average undergraduate student. A course focusing on creative AI has been developed to introduce deep learning from the practitioner perspective. Specifically, the application of deep learning in human creative activities, such as in art, music, and multimedia, forms the basis of our educational approach. The major topics of this course are presented, along with the software tools being utilized. Sample laboratory assignments and projects are introduced, and the results of measuring various student outcomes across two semesters are presented. Overall, the use of deep learning in applications mimicking human creativity can serve the purposes of getting students excited about machine learning and also help enhance their core knowledge of programming and the utilization of standard library tools.

Original languageAmerican English
Title of host publicationSIGITE 2019 - Proceedings of the 20th Annual Conference on Information Technology Education
PublisherAssociation for Computing Machinery, Inc
Pages49-54
Number of pages6
ISBN (Electronic)9781450369213
DOIs
StatePublished - Sep 26 2019
Event20th Annual Conference on Information Technology Education, SIGITE 2019 - Tacoma, United States
Duration: Oct 3 2019Oct 5 2019

Publication series

NameSIGITE 2019 - Proceedings of the 20th Annual Conference on Information Technology Education

Conference

Conference20th Annual Conference on Information Technology Education, SIGITE 2019
Country/TerritoryUnited States
CityTacoma
Period10/3/1910/5/19

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Education

Keywords

  • Artificial Neural Network
  • Creative Artificial Intelligence (AI)
  • Deep Learning
  • Generative Adversarial Neural Network (GAN)
  • Machine Learning

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