700.370 (24S) Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation

Sommersemester 2024

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Erster Termin der LV
11.03.2024 14:00 - 16:00 Online in the moodle Off Campus
Nächster Termin:
29.04.2024 08:15 - 09:45 HS 11 On Campus
Nächster gültiger Termin:
29.04.2024 14:00 - 16:00 Online in the moodle Off Campus

Überblick

Lehrende/r
LV-Titel englisch Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation
LV-Art Seminar (prüfungsimmanente LV )
LV-Modell Blended-Learning-Lehrveranstaltung
Online-Anteil 45%
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 3.0
Anmeldungen 10 (20 max.)
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 11.03.2024
eLearning zum Moodle-Kurs
Seniorstudium Liberale Ja

Zeit und Ort

Liste der Termine wird geladen...

LV-Beschreibung

Intendierte Lernergebnisse

In this seminar, students will get familiar with selected fundamentals of Self-Driving Vehicles. In particular, each student will deeply study one or more papers related to a subject related to data mining and/or pattern recognition in the frame of self-driving vehicles.

Lehrmethodik inkl. Einsatz von eLearning-Tools

GLOBAL PLAN:

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1) Kick-Off Meeting (at Semester begin): introductory presentation,  topics selection by the student, brief overview of related papers and documents.

1) A comprehensive Tutorial Part on "Fundamentals of DATA ANALYTICS" (3-4 sessions at semester beginn)

2) Intermediate presentations (after 3-4 Weeks): here students present their global plannings and their first rough ideas. A related feedback is provided.

3) Final presentations: 1st-2nd week of June 

4) Final paper/report submission: around last week of June or first half of July

Inhalt/e

Selected topics (not exhaustive):
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#  Learning Driver Behavior Models from Traffic Observations for DecisionMaking and Planning

#  Driver Behavior Profiling Using Smartphones

#  Modeling the Driving Behavior of Electric Vehicles Using Smartphones and Neural Networks

# The Impact of an Anticipatory Eco-Driver Assistant System in Different Complex Driving Situations on the Driver Behavior

#  Velocity-Based Driver Intent Inference at Urban Intersections in the Presence of Preceding Vehicles

#  The Attentive Co-Pilot: Towards a Proactive Biologically-Inspired Advanced Driver Assistance System.




 


Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Prüfungsmethode/n

                                 


Prüfungsinhalt/e

                           

                                     



Beurteilungskriterien/-maßstäbe

                                  

      



Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 22W.1)
    • Fach: Bachelorarbeit Ingenieurwissenschaften (Pflichtfach)
      • 14a.1 Seminar aus dem Bereich Ingenierwissenschaften ( 0.0h SE / 3.0 ECTS)
        • 700.370 Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation (2.0h SE / 3.0 ECTS)
          Absolvierung im 6. Semester empfohlen
  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Fach: Bachelorarbeit Ingenieurwissenschaften (Pflichtfach)
      • 13a.1 Seminar aus dem Bereich Ingenieurwissenschaften ( 2.0h SE / 3.0 ECTS)
        • 700.370 Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation (2.0h SE / 3.0 ECTS)
          Absolvierung im 6. Semester empfohlen
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.370 Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation (2.0h SE / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.370 Seminar in LLM (large language models) application for Data Analytics in Intelligent Transportation (2.0h SE / 3.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2022
  • 700.370 SE Seminar on Data Analytics in Intelligent Transportation (2.0h / 3.0ECTS)
Sommersemester 2021
  • 700.370 VS Seminar on "DATA ANALYTICS" and "PATTERN RECOGNITION" in Intelligent Transportation (2.0h / 4.0ECTS)
Sommersemester 2020
  • 700.370 VS Seminar on "DATA ANALYTICS" and "PATTERN RECOGNITION" in Intelligent Transportation (2.0h / 4.0ECTS)
Sommersemester 2019
  • 700.370 SE Seminar on Data Science in Intelligent Transportation (2.0h / 3.0ECTS)
Sommersemester 2017
  • 700.370 SE Seminar on Data mining and Pattern Recognition in Intelligent Vehicle Technologies (2.0h / 4.0ECTS)
Sommersemester 2016
  • 700.370 SE Seminar on Data mining and Pattern Recognition in Intelligent Vehicle Technologies (2.0h / 4.0ECTS)
Sommersemester 2015
  • 700.370 SE Seminar on Data mining and Pattern Recognition in Intelligent Vehicle Technologies (2.0h / 4.0ECTS)
Sommersemester 2014
  • 700.370 SE Seminar on Data mining and Pattern Recognition in Intelligent Vehicle Technologies (2.0h / 4.0ECTS)
Sommersemester 2013
  • 700.370 SE Seminar on Pattern Recognition in Intelligent Vehicle Technologies (2.0h / 4.0ECTS)