The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses.
In the first Data Challenge 1, students will get the possibility to apply the methods and techniques acquired during the first year of the program on a large, complex dataset. The students will be given a large, structured dataset, several specific analysis questions about this dataset, and a proposed analysis approach for each question (i.e., particular analysis techniques to apply). The task for the students is to technically realize these analyses by identifying and familiarizing themselves with the right software tools for this analysis, implementing the analysis in a repeatable form, and reflecting on the validity of their results and the suitability of their analysis approach. An important element in this course will be the actual handling of large data being stored in various formats (files, relational databases, object databases, etc.), the pre-processing of data to be usable for the analysis, and the storage of analysis results in a suitable data format.
- Renata Medeiros de Carvalho - Position: UD Room: MF 7.067 Tel (internal): 4144 Links: Courses External assignments Projects Publications External links: Google Scholar page Scopus page ORCID page DBLP page TU/e page Recent courses Recent external assignments Recent projects Recent publications
- Mitchel Brunings - Position: PhD TA Room: MF 7.070 Tel (internal): Links: Courses Presentations Projects Publications External links: Google Scholar page Scopus page DBLP page Awards Recent courses Recent presentations Recent projects Recent publications
- Azadeh Mozafari Mehr - Position: PhD Student Room: MF 7.117 Tel (internal): 6320 Links: Courses Presentations Projects Publications External links: Scopus page ORCID page DBLP page TU/e page Recent courses Recent presentations Recent projects Recent publications