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Teaching data science : core learning outcomes and topics for an introductory course.

Jeffrey S. Saltz, PhD, Associate Professor, and Jeffrey M. Stanton, PhD, Professor, in the School of Information Studies at Syracuse University, discuss their experience and expertise teaching data science, including what data science is and fields related to it; "flavors" of data science...

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Bibliographic Details
Other Authors: Goldes, Susannah (Speaker), Saltz, Jeffrey (Academic.), Stanton, Jeffrey (Academic.)
Format: Video
Language:English
Language Notes:Closed-captions in English.
Published: London : SAGE Publications Ltd, 2018.
Subjects:
Big data.
Machine learning.
Data mining.
Quantitative research.
Données volumineuses.
Apprentissage automatique.
Exploration de données (Informatique)
Recherche quantitative.
Big data
Data mining
Machine learning
Quantitative research
Online Access:Connect to this streaming video
Description
Summary:Jeffrey S. Saltz, PhD, Associate Professor, and Jeffrey M. Stanton, PhD, Professor, in the School of Information Studies at Syracuse University, discuss their experience and expertise teaching data science, including what data science is and fields related to it; "flavors" of data science courses; roles of data science; learning outcomes, technical tools and essentials; a starter data science toolkit; power tools: Python, R, and cloud services; structure of a sample introductory data science course; reading, transforming, and munging data; statistics, visualization, and data-driven maps; and ethics in data science. A Q&A session follows.
Physical Description:1 online resource (1 video file (00:48:58)) : sound, colour
ISBN:9781526498595
1526498596