700.373 (19S) Lab on Machine Learning and Applications in Intelligent Vehicles
Overview
- Lecturer
- Course title german Lab on Machine Learning and Applications in Intelligent Vehicles
- Type Course (continuous assessment course )
- Hours per Week 2.0
- ECTS credits 3.0
- Registrations 20 (20 max.)
- Organisational unit
- Language of instruction English
- Course begins on 05.06.2019
- eLearning Go to Moodle course
Time and place
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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
Pygame (game engine)
Tensorboard
Blender
Course content
- Self driving car simulation
- Visual reasoning
- Natural Language Processing
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
- Masterstudium 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)
- Masterstudium 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)
- Masterstudium 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)
- Masterstudium 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)
- Masterstudium 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)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Major Field of Specialization (Intelligent Transportation Systems)
(Compulsory subject)
-
1.4-1.5 Exercises or Lab (
4.0h KU / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
1.4-1.5 Exercises or Lab (
4.0h KU / 6.0 ECTS)
-
Subject: Major Field of Specialization (Intelligent Transportation Systems)
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Additional Technical Module II
(Compulsory subject)
-
3.4-3.5 Exercises or Lab (
4.0h KU / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
3.4-3.5 Exercises or Lab (
4.0h KU / 6.0 ECTS)
-
Subject: Additional Technical Module II
(Compulsory subject)
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 2021
- 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 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)