Arvutiteaduse instituut
  1. Kursused
  2. 2024/25 kevad
  3. Pervasiivse andmeteaduse seminar (LTAT.06.010)
EN
Logi sisse

Pervasiivse andmeteaduse seminar 2024/25 kevad

  • General
  • Lectures
  • Projects
  • Material and Examples
  • Message board

Readings:

  • Pervasive data science
  • Pervasive data science on the edge

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.

  • 10.02 Introduction to Pervasive Data Science (Slides)
  • 24.02 No-session
  • 03.03 Project selection and Lecture PhD student presentation - "Seamless integration of light sensors with nanodrones for produce quality estimation" - Presentation delivered in ACM IoT 2023 (Slides) and "ContextLLM: ContextLLM: Meaningful Context Reasoning from Multi-Sensor and Multi-Device Data Using LLMs" - Presentation delivered in ACM HotMobile 2025 (Slides)
  • 10.03 Student project understanding (Student checking point 1) and obtaining equipment (Pick up point: 3044)
  • 17.03 Lecture "Statistical analysis over data" and example through a PhD student presentation (Slides) and "PhD student presentation - HIPPO: Pervasive Hand-grip Estimation from Everyday Interactions" - Presentation delivered in ACM UbiComp 2023 (Slides)
  • 24.03 Lecture "No session: but please arrange a face-to-face meeting with your co-supervisor
  • 31.03 Update of prototype development and Lecture "PhD student presentation - Smart Plants on Wheels" - Content from our paper published in IEEE Pervasive Computing Magazine (Slides)
  • 07.04 Student checking point 2
  • 21.04 Lecture "How to present in a conference?" (Slides)
  • 28.04 Lecture "How to perform a (concise) literature review?" (Slides)
  • 05.05 No-session: but please arrange a face-to-face meeting with your co-supervisor
  • 12.05 Student checking point (Re-scheduled due to Turing Awardee talk)
  • 19.05 Student checking point
  • 26.05 Course ended with agreement on deliverables. Thank you for participating!
  • Arvutiteaduse instituut
  • Loodus- ja täppisteaduste valdkond
  • Tartu Ülikool
Tehniliste probleemide või küsimuste korral kirjuta:

Kursuse sisu ja korralduslike küsimustega pöörduge kursuse korraldajate poole.
Õppematerjalide varalised autoriõigused kuuluvad Tartu Ülikoolile. Õppematerjalide kasutamine on lubatud autoriõiguse seaduses ettenähtud teose vaba kasutamise eesmärkidel ja tingimustel. Õppematerjalide kasutamisel on kasutaja kohustatud viitama õppematerjalide autorile.
Õppematerjalide kasutamine muudel eesmärkidel on lubatud ainult Tartu Ülikooli eelneval kirjalikul nõusolekul.
Courses’i keskkonna kasutustingimused