Data Analytics and Communication
Faculteit | Science and Engineering |
Jaar | 2020/21 |
Vakcode | WBAI011-05 |
Vaknaam | Data Analytics and Communication |
Niveau(s) | bachelor |
Voertaal | Engels |
Periode | semester I b |
ECTS | 5 |
Rooster | rooster.rug.nl |
Uitgebreide vaknaam | Data Analytics and Communication | ||||||||||||
Leerdoelen | At the end of this course, the student is able to: - develop experiment/analysis design for reproducible science - know how to create reproducible workflows - recognize questionable research practices and invalid conclusions - tell accurate and convincing stories about collected data - use computer-intensive methods for data analysis - compare different (statistical) models |
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Omschrijving | While people could easily be replaced in running statistical tests on that, interpreting the results and communicating those to others are much more difficult skills that cannot be mastered by a computer. In this course we develop these crucial skills. We think together about how to go about asking good questions for solving a scientific or societal problem, how to conduct reproducible research, and how to communicate the obtained results. This highly interactive course will provide the student with crucial skills for successfully completing a Bachelor project and for being an effective data scientist. | ||||||||||||
Uren per week | |||||||||||||
Onderwijsvorm |
Bijeenkomst (S), Hoorcollege (LC), Opdracht (ASM), Practisch werk (PRC)
(Verplichte aanwezigheid.) |
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Toetsvorm |
Practisch werk (PR), Presentatie (P), Schriftelijk tentamen (WE)
(Dit is een cursus waarbij je vanaf het begin aan het werk bent en de practica zijn heel belangrijk. Het cijfer bestaat uit deelname in de les (5%), gesloten boek tentamen (50%), presentatie over een statistische toets (5%) en practica (40%)) |
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Vaksoort | bachelor | ||||||||||||
Coördinator | dr. M.K. van Vugt | ||||||||||||
Docent(en) | dr. M.K. van Vugt | ||||||||||||
Verplichte literatuur |
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Entreevoorwaarden | Mandatory: Statistics (WBAI049-05).
If the mandatory requirements are not met, only the Board of Examiners of the AI BSc may grant an exemption. Exchange students are assumed to have gone through this through their Learning Agreement; pre-master's students through the Board of Admissions - other external students are judged case-by-case. |
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Opmerkingen | This course was registered last year with course code WBAI17001 Artificial Intelligence (BSc) is a Fixed Quota (Numerus Fixus) programme. As a consequence, their courses (course code WBAI) are closed for students that are not registered under the AI BSc programme, unless the course is part of the mandatory curriculum of their programme. If you wish to take this course in your minor – or as part of a so-called ‘unofficial’ pre-master’s – please use the official procedure through the Board of Examiners form. |
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Opgenomen in |
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