621.062 (20W) Introduction to Artificial Intelligence II

Wintersemester 2020/21

Registration deadline has expired.

First course session
06.10.2020 10:00 - 12:00 online Off Campus
... no further dates known

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.
Lecturer
Course title german Einführung in die Artificial Intelligence II
Type Lecture - Course (continuous assessment course )
Course model Online course
Hours per Week 2.0
ECTS credits 3.0
Registrations 22 (30 max.)
Organisational unit
Language of instruction German
Course begins on 06.10.2020
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

Students should recognize the issue of uncertainty inherent in many Artificial Intelligence applications, understand basic methods for dealing with this issue and learn to adopt and comprehend concrete algorithms that implement these methods. The focus in the first half of the semester will be on reasoning under uncertainty, whereas the second half will deal with learning.

Teaching methodology including the use of eLearning tools

Lecture mixed with practical home and in-class exercises. Slides will be in English. Teaching language will be German unless there are non-German-speaking participants, otherwise English.


eLearning

Moodle

Course content

Provides an introduction to selected methods for dealing with uncertainty in Artificial Intelligence and Knowledge-Based Systems.

Topics

  • Uncertainty in AI Systems
  • Bayesian Inference and Bayesian Networks
  • Unsupervised Machine Learning
  • Supervised Machine Learning

Literature

Adnan Darwiche. Modeling and Reasoning with Bayesian Networks. Cambridge University Press. 2009 P. 

Tan, M. Steinbach, V. Kumar. Introduction to Data Mining. Pearson. 2006 

Stuart Russell and Peter Norvig: Artificial Intelligence: A modern approach. Prentice Hall, 2009 

Judea Pearl: Probabilistic Reasoning in Intelligent Systems - Networks of Plausible Inference. Morgan Kaufmann Publishers, Inc. 1988 

D. Koller, N. Friedman. Probabilistic Graphical Models: Principles and Techniques. The MIT Press. 2009 

D. Barber. Bayesian Reasoning and Machine Learning. Cambridge University Press. 2012 

T. Mitchell. Machine Learning. McGraw Hill. 1997

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 scheme

Position in the curriculum

  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 19W.2)
    • Subject: Vertiefung Informatik (Compulsory elective)
      • 7.3 Einführung in die Artificial Intelligence II ( 2.0h VC / 3.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 3.0 ECTS)
          Absolvierung im 4., 5., 6. Semester empfohlen
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Medieninformatik (Compulsory elective)
      • 4.2 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Natural Language Processing (Compulsory elective)
      • 5.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Software Development (Compulsory elective)
      • 6.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Business Informatics (Compulsory elective)
      • 7.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Media Informatics (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Natural Language Processing (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Software Development (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Business Informatics (Compulsory elective)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Master's degree programme Applied Informatics (SKZ: 911, Version: 13W.1)
    • Subject: Vertiefung Informatik (Compulsory subject)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information Management (SKZ: 922, Version: 13W.2)
    • Subject: Informatik (Compulsory subject)
      • 1.1 Knowledge Engineering für Informationsmanagement ( 2.0h KS / 4.0 ECTS)
        • 621.062 Introduction to Artificial Intelligence II (2.0h VC / 4.0 ECTS)

Equivalent courses for counting the examination attempts

Sommersemester 2024
  • 621.064 VC Introduction to Artificial Intelligence 2 - Group A (2.0h / 3.0ECTS)
  • 621.066 VC Introduction to Artificial Intelligence 2 - Group B (2.0h / 3.0ECTS)
Wintersemester 2023/24
  • 621.062 VC Introduction to Artificial Intelligence 2 (2.0h / 3.0ECTS)
Sommersemester 2023
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Wintersemester 2022/23
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Sommersemester 2022
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Wintersemester 2021/22
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Sommersemester 2021
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Sommersemester 2020
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)
Wintersemester 2019/20
  • 621.062 VC Einführung in die Artificial Intelligence II (2.0h / 3.0ECTS)