An Experience-Centered Approach to Training Effective Data Scientists.

Saved in:
Bibliographic Details
Title: An Experience-Centered Approach to Training Effective Data Scientists.
Authors: Rodolfa KT; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania., Unanue A; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Department of Mathematics, Instituto Tecnológico Autónomo de México, Mexico City, Mexico., Gee M; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois., Ghani R; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania.; Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Source: Big data [Big Data] 2019 Dec; Vol. 7 (4), pp. 249-261.
Publication Type: Journal Article
Journal Info: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 101631218 Publication Model: Print Cited Medium: Internet ISSN: 2167-647X (Electronic) Linking ISSN: 21676461 NLM ISO Abbreviation: Big Data Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 31860342
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: An Experience-Centered Approach to Training Effective Data Scientists.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Rodolfa+KT%22">Rodolfa KT</searchLink>; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania.<br /><searchLink fieldCode="AU" term="%22Unanue+A%22">Unanue A</searchLink>; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Department of Mathematics, Instituto Tecnológico Autónomo de México, Mexico City, Mexico.<br /><searchLink fieldCode="AU" term="%22Gee+M%22">Gee M</searchLink>; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.<br /><searchLink fieldCode="AU" term="%22Ghani+R%22">Ghani R</searchLink>; Center for Data Science and Public Policy, Computer Science Department and Harris School of Public Policy, University of Chicago, Chicago, Illinois.; Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania.; Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101631218%22">Big data</searchLink> [Big Data] 2019 Dec; Vol. 7 (4), pp. 249-261.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Mary+Ann+Liebert%2C+Inc%22">Mary Ann Liebert, Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101631218 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>2167-647X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2221676461%22">21676461 </searchLink><i>NLM ISO Abbreviation: </i>Big Data <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=31860342
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1089/big.2019.0100
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 249
    Titles:
      – TitleFull: An Experience-Centered Approach to Training Effective Data Scientists.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Rodolfa KT
      – PersonEntity:
          Name:
            NameFull: Unanue A
      – PersonEntity:
          Name:
            NameFull: Gee M
      – PersonEntity:
          Name:
            NameFull: Ghani R
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: 2019 Dec
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-electronic
              Value: 2167-647X
          Numbering:
            – Type: volume
              Value: 7
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Big data
              Type: main
ResultId 1