Foundations of Data Analytics (2IAB1) 2026-2027
General learning goals
Tag: 2IAB1
Foundations of Data Analytics (2IAB1) 2025-2026
General learning goals
Foundations of Data Analytics (2IAB1) 2024-2025
General learning goals Use basic statistical concepts and techniques and perform appropriate statistical tests Choose and apply suitable visualization techniques Analyze and model data using linear regression, clustering, decision tree mining and association rules learning Read and make simple database schemes and simple queries to a database. Clean data, choose and apply data transformations, data Read More …
Foundations of Data Analytics (2IAB1) 2023
Learning goals Working with data data exploration statistical techniques data visualisation data mining data organization and data retrieval Programming (customizable, reproducible) Communication skills (visualisations, a poster and a pitch in the assignments) Systematic way to approach problems (“scientific method”)
Ava Swevels
Position: PhD Student Room: MF 7.060 Tel (internal): Links: CoursesPresentationsProjectsPublications External links: Scopus pageORCID pageDBLP pageTU/e page Recent courses Recent presentations Recent projects Recent publications
Erandi (Gonzalez) Miranda
Erandi (Gonzalez) Miranda is a lecturer assistant at the PA group. Position: Lecturer assistant Room: MF 7.117 Tel (internal): Links: Courses External links: TU/e page Recent courses
Eva Klijn
Position: PhD-TA Room: MF 7.060 Tel (internal): 3173 Links: Courses Presentations Projects Publications External links: Scopus page ORCID page DBLP page TU/e page Awards Recent courses Recent presentations Recent projects Recent publications
Natalia Sidorova
Dr. Natalia Sidorova is assistant professor at the PA group. She actively works on topics related to process modeling and verification. The application domains include business processes and distributed systems. She has published more than 70 conference and journal papers. She is active in the Health and Wellbeing Action Line of EIT ICT Labs, taking Read More …
Mitchel Brunings
Position: PhD-TA Room: MF 7.060 Tel (internal): Links: Courses Presentations Projects Publications External links: Google Scholar page Scopus page DBLP page TU/e page Awards Recent courses Recent presentations Recent projects Recent publications
Eric Verbeek
Eric is the scientific programmer in the PA group. As such, he is the custodian of the process mining framework ProM. In you want access to the ProM repository, or have any questions related to ProM and its development, ask Eric. Recently, he has been working on a decomposition framework for both process discovery as Read More …