[ 536AIBAHO1U20 ] UE (*)Hands-on AI I
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| Workload |
Ausbildungslevel |
Studienfachbereich |
VerantwortlicheR |
Semesterstunden |
Anbietende Uni |
| 1,5 ECTS |
B1 - Bachelor 1. Jahr |
Artificial Intelligence |
Johannes Brandstetter |
1 SSt |
Johannes Kepler Universität Linz |
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| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Artificial Intelligence 2020W |
| Ziele |
(*)Hands-on AI I provides a first direct contact with various AI approaches (no previous knowledge is required). The focus of this course is mainly put on Artificial Neural Networks and Deep Learning. Objectives are practical applications and getting an overview of Deep Learning approaches. All of the shown techniques will be taught in much greater detail later in the studies.
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| Lehrinhalte |
(*)- Handling and understanding of different kinds of data sets
- Visualization, dimensionality reduction and clustering of data
- Moving from Linear Regression to Logistic Regression and Artificial Neural Networks
- Understanding gradient descent
- Using Deep Learning frameworks like PyTorch
- Playing around with the first Artificial Neural Networks
- Introducing Convolutional Neural Networks
- Tips and tricks for making networks learn (batch normalization, dropout, transfer learning, etc.)
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| Beurteilungskriterien |
(*)Online Assignments
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| Abhaltungssprache |
Englisch |
| Lehrinhalte wechselnd? |
Nein |
| Äquivalenzen |
(*)in collaboration with 536AIBAHO1V20: VL Hands-on AI I (1.5 ECTS) equivalent to
536AIBAHO1K19: KV Hands-on AI I (3 ECTS)
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| Präsenzlehrveranstaltung |
| Teilungsziffer |
35 |
| Zuteilungsverfahren |
Direktzuteilung |
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