Data Analytics and Communication

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
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.)
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%))
Vaksoort	bachelor
Coördinator	dr. M.K. van Vugt
Docent(en)	dr. M.K. van Vugt
Verplichte literatuur	Titel Auteur ISBN Prijs Readings on Nestor
Entreevoorwaarden	Mandatory: Statistics (WBAI049-05). While formally mandatory - the grades for Statistics will not be in before the course starts. Students are not checked for this entry requirement, making it more of a semi-mandatory requirement / advice. This advice is a bit stronger than other listed requirement advice, however. 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.
Opmerkingen	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.
Opgenomen in	Opleiding Jaar Periode Type BSc Artificial Intelligence 2 semester I b verplicht BSc Courses for Exchange Students: AI - Computing Science - Mathematics - semester I b Pre-master/Fast-track for MSc AI - CCS – CS - Math  (Artificial Intelligence) - semester I b -