Students gain insight in basic techniques for processing large amounts of data in an efficient, reliable, and consistent way.
Students develop skills in understanding, interpreting, and documenting data and information in the context of realistic scenarios.
Students get understanding of the data life cycle and develop skills for structuring their solutions of practical problems along the phases of the data life cycle.
Students apply data analytics techniques to realistic data sets in which they can recognize the demands within their area of specialization.
Students obtain basic knowledge of statistical concepts and techniques and develop skills to apply them in practice.
Students learn to implement their solutions for data analytics problems in a programming language (Python), and apply a structured and systematic approach to data processing.
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 ... Renata Medeiros de Carvalho - Position: UD Room: MF 7.067 Tel (internal): 4144 Links: Courses External assignments Projects Publications External links: Scopus 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: Recent courses Recent presentations Recent projects Recent publications Eva Klijn - Position: PhD TA Room: MF 7.062 Tel (internal): 3173 Links: Courses Presentations Projects Publications External links: TU/e page Recent courses Recent presentations Recent projects Recent publications