LTAT.06.010 Pervasive Data Science Seminar
- Lectures: Narva mnt 18 - Room 1022
- Schedule: Monday 16:15 - 18:00, course starts week 2 and last until week 16
- 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 air and aquatic 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 machine and deep learning techniques in resource constrained devices, where processing power, energy and storage are limited. Besides this, the seminar also introduces to students with tools and methodologies for data sampling and acquisition, through users studies, surveys and other human-computer sampling methods. Participants are expected to give oral presentations on a particular topic and solve practical tasks using R, MatLab or Python.
- Lectures are in person in the lecture room (unless restrictions are given by Delta admin or agreed a priori with the lecturer)