Inhalt

[ 536AIBAHO1U20 ] UE (*)Hands-on AI I

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS B1 - Bachelor 1. Jahr Artificial Intelligence Johannes Brandstetter 1 SSt Johannes Kepler Universität Linz
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.
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.)
Beurteilungskriterien (*)Online Assignments
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)
Präsenzlehrveranstaltung
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung