700.373 (21S) Lab on Machine Learning and Applications in Intelligent Vehicles
Overview
Due to the COVID-19 pandemic, it may be necessary to make changes to courses and examinations at short notice (e.g. cancellation of attendance-based courses and switching to online examinations).
For further information regarding teaching on campus, please visit: https://www.aau.at/en/corona.
For further information regarding teaching on campus, please visit: https://www.aau.at/en/corona.
- Lecturer
- Course title german Lab on Machine Learning and Applications in Intelligent Vehicles
- Type Course (continuous assessment course )
- Course model Online course
- Hours per Week 2.0
- ECTS credits 3.0
- Registrations 19 (20 max.)
- Organisational unit
- Language of instruction Englisch
- Course begins on 24.03.2021
- eLearning Go to Moodle course
Time and place
Please note that the currently displayed dates may be subject to change due to COVID-19 measures.
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Course Information
Intended learning outcomes
This lab is a complementary to 700.340 (19S) Machine Learning in Intelligent Transportation.
students will learn how to implement the state of the art deep learning models using tensorflow and keras
Teaching methodology including the use of eLearning tools
Python
Tensorflow
Keras
Unity/Unreal Simulation
Tensorboard
Course content
- Self driving car simulation
- Visual reasoning
- Natural Language Processing
- https://www.youtube.com/watch?v=Fgv5H_Parwc&list=PLUAvE4k0OWwdbKM7G532jd_jowoDmue2o
Prior knowledge expected
Mandatory:
Knowledge in Object Oriented Programming Concepts
Intermediate level of python programming skills
Basic skills in C++
Basic knowledge in Deep Learning
Nice to have:
Experience in Tensorflow/Keras and or Pytorch
Examination information
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.
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- Master's degree programme Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Master's degree programme Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Master's degree programme Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Master's degree programme Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Master's degree programme Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
Equivalent courses for counting the examination attempts
-
Sommersemester 2024
- 700.373 KS Lab: Neurocomputing in Robotics and Intelligent Transportation (2.0h / 3.0ECTS)
-
Sommersemester 2023
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2022
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2020
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2019
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2018
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2017
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2016
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2015
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2014
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2013
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)