LTAT.06.010 Pervasive Data Science Seminar
- Lectures: J. Liivi 2 - 611
- Schedule: Friday 12:15-16:00
- Coordinator: Huber Flores
Pervasive Data Science is an emerging research field in the intersection of pervasive computing and data science that builds on the increased proliferation of sensors into everyday environments. These sensors produce large volumes of complex, real-time data streams, which are opening scientific investigations at an unprecedented scale. Examples of the adoption of pervasive computing and sensors abound, with pollution monitoring, patient health monitoring and autonomous drone systems, being examples of domains benefiting from pervasive data.
The pervasive data science seminar provides an overview of techniques that can be used to analyze large scale sensor datasets, and principles to execute sophisticated analysis techniques in resource constrained devices, where processing power, energy and storage are limited. The main goal is to learn to carry out pervasive data science with common methods of regression, machine learning, and deep learning. Participants are expected to give oral presentations on a particular topic and solve practical tasks using R, MatLab or Python.