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Guide to Teaching Data Science - An Interdisciplinary Approach (Hardcover, 1st ed. 2023)
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Guide to Teaching Data Science - An Interdisciplinary Approach (Hardcover, 1st ed. 2023)
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Data science is a new field that touches on almost every domain of
our lives, and thus it is taught in a variety of environments.
Accordingly, the book is suitable for teachers and lecturers in all
educational frameworks: K-12, academia and industry. This book aims
at closing a significant gap in the literature on
the pedagogy of data science. While there are many
articles and white papers dealing with the curriculum of data
science (i.e., what to teach?), the pedagogical aspect of the field
(i.e., how to teach?) is almost neglected. At the same time, the
importance of the pedagogical aspects of data science increases as
more and more programs are currently open to a variety of people.
This book provides a variety of pedagogical discussions and
specific teaching methods and frameworks, as well as includes
exercises, and guidelines related to many data science concepts
(e.g., data thinking and the data science workflow), main machine
learning algorithms and concepts (e.g., KNN, SVM, Neural Networks,
performance metrics, confusion matrix, and biases) and data science
professional topics (e.g., ethics, skills and research approach).
Professor Orit Hazzan is a faculty member at the
Technion’s Department of Education in Science and Technology
since October 2000. Her research focuses on computer science,
software engineering and data science education. Within this
framework, she studies the cognitive and social processes on the
individual, the team and the organization levels, in all kinds of
organizations. Dr. Koby Mike is a Ph.D. graduate from
the Technion's Department of Education in Science and Technology
under the supervision of Professor Orit Hazzan. He continued his
post-doc research on data science education at the Bar-Ilan
University, and obtained a B.Sc. and an M.Sc. in Electrical
Engineering from Tel Aviv University.
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