{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108021"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108021","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"LiveDataLab: A cloud-based platform for data science education","abstract":"The growth of the “big data” industry has created an urgent need for educating a large number of data scientists and engineers. However, learning practical data science skills requires hands-on experience with large, real-world datasets, which is difficult to offer at scale due to hardware and cost limitations. In this thesis, we present LiveDataLab, a novel cloud-based solution enabling deployment of hands-on assignments with large, real-world datasets and integration of data science education, research, and applications together in one ecosystem. LiveDataLab provides a novel project-based learning platform, alongside open leaderboard competitions, course assignment hosting, and auto-grading abilities. All of these applications are powered by a novel auto-scaling cloud backbone enabling these capabilities at relatively low cost. Additionally, LiveDataLab simultaneously serves as a platform supporting data science research via its integration with large, real-world datasets. LiveDataLab provides the ability to handle the growing demand and necessity for data science education, support data science research, and enable data science applications all in one singular platform. Ultimately, LiveDataLab brings learners, educators, researchers, and application developers together on a single unified platform to collaborate in a highly efficient big data ecosystem.","abstract_html":"The growth of the “big data” industry has created an urgent need for educating a large number of data scientists and engineers. However, learning practical data science skills requires hands-on experience with large, real-world datasets, which is difficult to offer at scale due to hardware and cost limitations. In this thesis, we present LiveDataLab, a novel cloud-based solution enabling deployment of hands-on assignments with large, real-world datasets and integration of data science education, research, and applications together in one ecosystem. LiveDataLab provides a novel project-based learning platform, alongside open leaderboard competitions, course assignment hosting, and auto-grading abilities. All of these applications are powered by a novel auto-scaling cloud backbone enabling these capabilities at relatively low cost. Additionally, LiveDataLab simultaneously serves as a platform supporting data science research via its integration with large, real-world datasets. LiveDataLab provides the ability to handle the growing demand and necessity for data science education, support data science research, and enable data science applications all in one singular platform. Ultimately, LiveDataLab brings learners, educators, researchers, and application developers together on a single unified platform to collaborate in a highly efficient big data ecosystem.","abstract_has_math":false,"creators":["Green, Aaron"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Zhai, ChengXiang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-26T21:57:59Z","date_published":"2020-08-26T21:57:59Z","updated_at":"2026-07-22T22:24:47Z","subjects":["data science","computer science education","cloud computing","data science education"],"languages":["en"],"rights":["Copyright 2020 Aaron Green"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108021","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhai, ChengXiang"]},{"key":"dc:creator","label":"Author","values":["Green, Aaron"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-26T21:57:59Z","2020-05-11","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["data science","computer science education","cloud computing","data science education"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Aaron Green"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108021"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The growth of the “big data” industry has created an urgent need for educating a large number of data scientists and engineers. However, learning practical data science skills requires hands-on experience with large, real-world datasets, which is difficult to offer at scale due to hardware and cost limitations. In this thesis, we present LiveDataLab, a novel cloud-based solution enabling deployment of hands-on assignments with large, real-world datasets and integration of data science education, research, and applications together in one ecosystem. LiveDataLab provides a novel project-based learning platform, alongside open leaderboard competitions, course assignment hosting, and auto-grading abilities. All of these applications are powered by a novel auto-scaling cloud backbone enabling these capabilities at relatively low cost. Additionally, LiveDataLab simultaneously serves as a platform supporting data science research via its integration with large, real-world datasets. LiveDataLab provides the ability to handle the growing demand and necessity for data science education, support data science research, and enable data science applications all in one singular platform. Ultimately, LiveDataLab brings learners, educators, researchers, and application developers together on a single unified platform to collaborate in a highly efficient big data ecosystem.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-08-25 without embargo terms","The student, Aaron Green, accepted the attached license on 2020-05-08 at 15:33.","The student, Aaron Green, submitted this Thesis for approval on 2020-05-08 at 15:39.","This Thesis was approved for publication on 2020-05-11 at 14:29.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15302 on 2020-08-25 at 17:13:39","Made available in DSpace on 2020-08-26T21:57:59Z (GMT). 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In this thesis, we present LiveDataLab, a novel cloud-based solution enabling deployment of hands-on assignments with large, real-world datasets and integration of data science education, research, and applications together in one ecosystem. LiveDataLab provides a novel project-based learning platform, alongside open leaderboard competitions, course assignment hosting, and auto-grading abilities. All of these applications are powered by a novel auto-scaling cloud backbone enabling these capabilities at relatively low cost. Additionally, LiveDataLab simultaneously serves as a platform supporting data science research via its integration with large, real-world datasets. LiveDataLab provides the ability to handle the growing demand and necessity for data science education, support data science research, and enable data science applications all in one singular platform. 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