700.197 (21S) Tutorium in Machine Learning and Tensorflow Basics
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.
- Tutor/Tutors
- Course title german Tutorium in Machine Learning and Tensorflow Basics
- Type Tutorium
- Course model Online course
- Hours per Week 2.0
- ECTS credits 0.0
- Registrations 16
- Organisational unit
- Language of instruction English
- Course begins on 02.03.2021
- 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
Get to know and use Github, Pyhton and Machine Learning and Tensorflow Basics.
Teaching methodology including the use of eLearning tools
In the BBB room with theory and programming examples.
Course content
- Basics of the PYTHON language
- Overview of the main librairies: Tensorflow, Keras, Pytorch, ...
- Overview of main frameworks & models: Alexnet, VGG, ...
- Introduction to GitHub
- Input / Output management or accesses in Python
- Short introduction to GAN (Generative Adversarial networks)
- A few programming examples + small homework exercises
Prior knowledge expected
No previous experience required
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
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 17W.1)
-
Subject: Informationstechnische Vertiefung
(Compulsory elective)
-
10a.1 Grundlagen und Methoden der Simulationstechnik (
0.0h VC / 3.0 ECTS)
- 700.197 Tutorium in Machine Learning and Tensorflow Basics (2.0h TU / 0.0 ECTS) Absolvierung im 4. Semester empfohlen
-
10a.1 Grundlagen und Methoden der Simulationstechnik (
0.0h VC / 3.0 ECTS)
-
Subject: Informationstechnische Vertiefung
(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)
- 700.197 Tutorium in Machine Learning and Tensorflow Basics (2.0h TU / 0.0 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: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.197 Tutorium in Machine Learning and Tensorflow Basics (2.0h TU / 0.0 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: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.197 Tutorium in Machine Learning and Tensorflow Basics (2.0h TU / 0.0 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)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Free Electives
(Optional subject)
-
Free Electives (
0.0h XX / 6.0 ECTS)
- 700.197 Tutorium in Machine Learning and Tensorflow Basics (2.0h TU / 0.0 ECTS)
-
Free Electives (
0.0h XX / 6.0 ECTS)
-
Subject: Free Electives
(Optional subject)
Equivalent courses for counting the examination attempts
This course is not assigned to a sequence of equivalent courses