Readings:
Lectures
Lectures are in person (every Monday) - Lectures will be also available online (Zoom link) (Passcode: pds2021)
Lectures will take place following the (tentative) schedule below.
- 12.02 Introduction to Pervasive Data Science (Slides)
- 19.02 Lecture "How to conduct a feasibility study?" (Slides)
- 26.02 Lecture "Assigning projects and obtaining prototypes/samples" (Pick up point: 3045)
- 04.03 Lecture "Statistical analysis over data" (Slides)
- 11.03 Lecture "No session: but see invitation to data science seminar in the slides" (Slides)
- 18.03 Lecture "PhD student presentation - HIPPO: Pervasive Hand-grip Estimation from Everyday Interactions" - Presentation delivered in ACM UbiComp 2023 (Slides)
- 25.03 Student checking point 2 and Lecture "PhD student presentation - Seamless integration of light sensors with nanodrones for produce quality estimation" - Presentation delivered in ACM IoT 2023 (Slides)
- 01.04 No-session
- 08.04 PhD student presentation - Upscaling Fog Computing in Oceans for Underwater Pervasive Data Science using Low-Cost Micro-Clouds - Presentation delivered in ACM SenSys 2023 (Slides) and Lecture "How to present my research in a conference" (Slides)
- 15.04 Student checking point 2
- 22.04 Lecture "How to perform a (concise) literature review?" (Slides)
- 29.04 Student project development (no-session)
- 06.05 Presentation and agreement of final deliverables (Slides)
- 13.05 onward - Final presentations
Course is graded Pass or Fail based on deliverable quality (if not possible attending in-person meetings, please contact the lecturer at Room 3045, Delta)