Model Curricula for Data Science EDISON Data Science Framework
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| Publication date | 2017 |
| Book title | 2017 IEEE 9th International Conference on Cloud Computing Technology and Science |
| Book subtitle | CloudCom 2017 : proceedings : 11-14 December 2017, Hong Kong, Hong Kong |
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| ISBN (electronic) |
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| Event | IEEE 9th International Conference on Cloud Computing Technology and Science |
| Pages (from-to) | 369-374 |
| Publisher | Los Alamitos, California: IEEE Computer Society |
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| Abstract |
This paper presents the Data Science Model Curriculum (MC-DS) that is based on the Data Science Competence Framework and Data Science Body of Knowledge defined in EDISON Data Science Framework (EDSF). MC-DS follows a competence-based curriculum design approach grounded in the Data Science competences (CD-DS) defined in EDSF and correspondingly defined Learning Outcomes (LO). The DSBoK provides a basis for structuring the proposed MC-DS by Knowledge Area Groups (KAG) defined in correspondence with the CF-DS competence groups. ECTS point allocation to specific areas is recommended for Master's and Bachelor's program covering professional profile groups.
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| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1109/CloudCom.2017.60 |
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