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Descripción
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| Data scientists are currently among the most demanded professionals in many spheres, including industries, governments, public sector, among others. This is due to several good reasons. Probably an important one of those reasons is the growing demand to find proper ways to face the challenges of establishing data-driven economies and societies. As academics and educationalists, but also Data Science professionals, we look at how to bring up this kind of specialists such that to meet the current shortages but also mid-term demands. In this position paper we deliberate about how to architect thematically, didactically, and organizationally a university program under the thematic umbrella of Data Science. We focus on the selection of learning units or disciplines to be covered in order to produce the M.Sci. and Ph.D. graduates who will be ready to face the future challenges in the mid-term perspective. We outline our recommendation on using learning tools and materials. We also concisely present the approach for stimulating competitive and cooperative atmosphere in the class that stimulates intensive collective and individual learning. We recommend to reinforce an academic program by involving industrial partners intensively in the process. We ground our deliberation on our experience in implementing relevant M.Sci. and Ph.D. programs in Data Science and Semantic Technologies. | |
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Internacional
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Si |
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Nombre congreso
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14th International Conference on ICT in Education, Research and Industrial Applications |
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Tipo de participación
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960 |
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Lugar del congreso
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Kyiv, Ukraine |
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Revisores
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Si |
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ISBN o ISSN
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1613-0073 |
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DOI
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Fecha inicio congreso
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14/05/2018 |
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Fecha fin congreso
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17/05/2018 |
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Desde la página
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734 |
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Hasta la página
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746 |
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Título de las actas
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Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer Volume II: Workshops. CEUR Workshop Proceedings 2104 |