Big Data in Sport Science and HMS

Uitgebreide vaknaam	Big Data in Sport Science and Human Movement Sciences
Leerdoelen	The students achieve theoretical knowledge of data analytics, machine learning, and data visualisation. Students learn to utilize their knowledge to analyse, interpret, merge and visualize complex data sets in human movement science context.
Omschrijving	This course is related to the courses Advanced Statistics (BWM136), Physiology of Training and Exercise (BWM134), Talent and Performance Optimization in Sports (BWM174), Introduction to dynamical systems (BWM142), Signal Acquisition (BWM145) The first six course weeks will have a central theme: (1) Introduction to Data Science & Data pre-processing, (2) Basics in Data bases & Big data, (3) Introduction to Machine Learning (4) Regressions (5) Classification & Clustering (6) Neuronal Networks & Reinforcement Learning. For each theme, an overview of theory will be given during the lecture. Each lecture is followed by a tutorial in which students will acquire different data science skills using published data sets. For each task students have to hand in their code. Based on their acquired knowledge the students have to carry out a research project in data science in groups with a maximum of 5 students. The first part of the group assignment is to formulate a research idea that will be presented in week 4 and hand in a research proposal. The research idea should include one of the methods presented in the lectures and tutorials. Data sets for the research ideas will be organized and pre-processed by the lecturer. Based on their research idea, students will complete a data science research project and present their result via a poster presentation at the end of the course Data sets can be related to any specialization of the masters (e. g.: Sports, Rehabilitation, Healthy aging)
Uren per week
Onderwijsvorm	opdrachten
Toetsvorm	zie studiegids (The assessment consists of four parts: Presentation of the research idea (20%) Research proposal (30%) Poster presentation of the research project (30%) Tutorial code (20%) Final grade needs to be at least 5.5 to pass.)
Vaksoort	Master
Coördinator	dr. M. Kempe
Docent(en)	F.R. Goes, MSc.
Verplichte literatuur	Titel Auteur ISBN Prijs Course reader and a list of scientific papers (t.b.a. on Nestor)
Entreevoorwaarden
Opmerkingen
Opgenomen in	Opleiding Jaar Periode Type MSc Human Movement Sciences 1 semester II b keuze MSc Sport Sciences 1 semester II b keuze