Course ObjectiveThe student has basic knowledge of the applicability of data science,
data analytics, machine learning and data visualization and storytelling
in sports and health.
The student knows possibilities and limitations of data science
techniques to process large data sets, including pre-processing.
The student can identify which data analytics methods to apply for an
analysis of complex data sets in human movement sciences.
The students knows how to interpret, visualize and communicate findings.
Course ContentIn this course students are introduced to the role of data science in
sports and health. The students will learn to apply data science
techniques and how to communicate their findings
Teaching MethodsLectures, work groups and practicals (obligatory) on data cleaning and
pre-processing, exploratory analysis, supervised/unsupervised machine
learning, data visualization and presentation.
Method of AssessmentAssignment including report and presentation of findings (50%)¶
Written final exam (50%)
Entry RequirementsKnowledge and understanding of programming in Matlab/R
LiteratureRecent articles in the field of sports and data science
Target AudienceStudents with an interest in data science, big data and data analytics
|Language of Tuition||English|
|Faculty||Fac. of Behavioural and Movement Science|
|Course Coordinator||dr. S. van der Zwaard|
|Examiner||dr. S. van der Zwaard|
You need to register for this course yourself
|Teaching Methods||Study Group, Lecture, Practical*|
*You cannot select a group yourself for this teaching method, you will be placed in a group.
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