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Article
Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course
Decision Sciences: Journal of Innovative Education
  • Daniel Asamoah, Wright State University - Main Campus
  • Ramesh Sharda
  • Amir H. Zadeh, Wright State University - Main Campus
  • Pankush Kalgotra
Document Type
Article
Publication Date
4-1-2017
Abstract

In this article, we present an experiential perspective on how a big data analytics course was designed and delivered to students at a major Midwestern university. In reference to the MSIS 2006 Model Curriculum, we designed this course as a level 2 course, with prerequisites in databases, computer programming, statistics, and data mining. Students in the class were mostly seniors or at the graduate level, and had a strong technical and quantitative background. We include details of concepts covered in the course, as well as summaries of four major sample course assignments used. Some of the concepts covered include large-scale data collection and management using the Hadoop ecosystem, stream mining, visual analytics, and social network analytics. Besides Hadoop, the course also introduced various IBM and Teradata big data tools. We show how the course modules align with the intended learning goals and course objectives. A post-course survey indicated that the structure and organization of the course helped students clearly and concisely assimilate the course content.

DOI
10.1111/dsji.12125
Citation Information
Daniel Asamoah, Ramesh Sharda, Amir H. Zadeh and Pankush Kalgotra. "Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course" Decision Sciences: Journal of Innovative Education Vol. 15 Iss. 2 (2017) p. 161 - 190 ISSN: 1540-4595
Available at: http://works.bepress.com/daniel_asamoah/18/