2023 ASEE Annual Conference & Exposition

Development of a Data Science Curriculum for an Engineering Technology Program

Presented at Engineering Technology Division (ETD) Technical Session 9

Data science has gained the attention of various industries, educators, parents, and students thinking about their future careers. Data science courses have been traditionally offered by statistics departments for a long time. The main objective of these courses is to examine the fundamental concepts and theories. However, teaching data science courses have moved to engineering branches, no longer bounded by statistics. There are various reasons for this transition. One is that the increased computational power and massive availability of the data make the application of statistical theories possible. The second one is the availability of libraries and models that allow the implementation of diverse solutions to problems. A typical data science curriculum covers the variety of topics, such as data processing, feature engineering, regression, classification, and natural language processing. In the last decades, data-driven models have significantly affected almost every industry. Various courses across the nation focus on introducing data science topics. However, a complete engineering technology curriculum has not been developed yet. This paper will discuss the details of introducing a new curriculum on data science in an electrical engineering technology program, including detailed course structures and projects.

Authors

Salih Sarp Old Dominion University [biography]

Salih Sarp is a Ph.D. student in the Electrical and Computer Engineering department at Old Dominion University, USA. Currently, he is developing AI applications and sensor fusion models. Previously, he received his BS degree in Electronics and Communication.
Dr. Murat Kuzlu http://orcid.org/https://0000-0002-8719-2353 Old Dominion University [biography]

Murat Kuzlu joined the Engineering Technology Department at Old Dominion University (ODU) as an Assistant Professor in 2018. He received his B.Sc., M.Sc., and Ph.D. degrees in Electronics and Telecommunications Engineering. He worked as a senior researcher at TUBITAK (Scientific and Technological Research Council of Turkey) between 2006 and 2011. Before joining ODU, he was a Research Assistant Professor at Virginia Tech’s Advanced Research Institute. His research interests include cyber-physical systems, smart cities, smart grids, artificial intelligence, and next-generation wireless networks.
Dr. Otilia Popescu Old Dominion University [biography]

Dr. Otilia Popescu received the Engineering Diploma and M.S. degree from the Polytechnic Institute of Bucharest, Romania, and the PhD degree from Rutgers University, all in Electrical and Computer Engineering. Her research interests are in the general areas of communication systems, control theory, signal processing and engineering education. She is currently an Associate Professor in the Department
of Engineering Technology, at Old Dominion University in Norfolk, Virginia, and serves as the Program Director for the Electrical Engineering Technology Program. In the past she has worked for the University of Texas at Dallas, University of Texas at San Antonio, Rutgers University, and Politehnica University of Bucharest. She is a senior member of the IEEE.
Dr. Vukica M. Jovanovic http://orcid.org/0000-0002-8626-903X Old Dominion University [biography]

Dr. Vukica Jovanovic is a Chair of the Department of Engineering Technology and Full Professor and Batten Endowed Fellow in Mechanical Engineering Technology Program. She holds a Ph.D. from Purdue University in Mechanical Engineering Technology, focusing on Digital Manufacturing
Zafer Acar

Download paper (689 KB)

Are you a researcher? Would you like to cite this paper? Visit the ASEE document repository at peer.asee.org for more tools and easy citations.

» Download paper

« View session