623.131 (12S) Selected Topics in Artificial Intelligence

Sommersemester 2012

Registration deadline has expired.

First course session
11.06.2012 10:00 - 12:00 HS 4 On Campus
... no further dates known

Overview

Lecturer
Course title german Selected Topics in Artificial Intelligence
Type Lecture - Colloquia (continuous assessment course )
Hours per Week 2.0
ECTS credits 3.0
Registrations 18
Organisational unit
Language of instruction English
Course begins on 10.06.2012

Time and place

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Course Information

Teaching methodology including the use of eLearning tools

Course comprises lectures interleaved with exercises Student's active participation is desirable and acknowledge in exam marks Students are offered to do a project in teams of up to three members, successfull project score bonus points taken into account in final exam

Course content

Advanced heuristic search methods

Topics

  • Machine learning from noisy data
  • Language processing with DCG grammars
  • Bayesian Networks
  • Qualitative Modeling and Reasoning

Teaching objective

Introduce some particularly useful and interesting methods of Artificial Intelligence Develop understanding of these techniques sufficient for application in practice

Prior knowledge expected

Basics of computer requirements Knowledge of some basics of Artificial Intelligence Basic knowledge of Prolog is helpful

Literature

Bratko, Prolog Programming for Artificial Intelligence, 4th Edition, Pearson Education, March 2011 (3rd edition of this book is also adequate) Additional: S. Russell, P. Norvig, Artificial Intelligence: a Modern Approach, 3rd. edition, Prentice-HAll, 2009. I.H. Witten, E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd edition. Elsevier, 2005.

Teaching methodology including the use of eLearning tools

Course comprises lectures interleaved with exercises Student's active participation is desirable and acknowledge in exam marks Students are offered to do a project in teams of up to three members, successfull project score bonus points taken into account in final exam

Course content

Advanced heuristic search methods

Topics

  • Machine learning from noisy data
  • Language processing with DCG grammars
  • Bayesian Networks
  • Qualitative Modeling and Reasoning

Teaching objective

Introduce some particularly useful and interesting methods of Artificial Intelligence Develop understanding of these techniques sufficient for application in practice

Prior knowledge expected

Basics of computer requirements Knowledge of some basics of Artificial Intelligence Basic knowledge of Prolog is helpful

Literature

Bratko, Prolog Programming for Artificial Intelligence, 4th Edition, Pearson Education, March 2011 (3rd edition of this book is also adequate) Additional: S. Russell, P. Norvig, Artificial Intelligence: a Modern Approach, 3rd. edition, Prentice-HAll, 2009. I.H. Witten, E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd edition. Elsevier, 2005.

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.

Assessment criteria / Standards of assessment for examinations

schriftlich

Assessment criteria / Standards of assessment for examinations

written

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Teacher training programme Computer Sciences and Computer Sciences Management (Secondary School Teacher Accreditation) (SKZ: 884, Version: 04W.7)
    • Stage two
      • Subject: Angewandte Informatik (LI 2.3) (Compulsory subject)
        • Ausgewählte Kapitel aus Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
          • 623.131 Selected Topics in Artificial Intelligence (2.0h VK / 3.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 09W.1)
    • Subject: Data and Knowledge Engineering (Compulsory subject)
      • Artificial Intelligence ( 2.0h VK / 4.0 ECTS)
        • 623.131 Selected Topics in Artificial Intelligence (2.0h VK / 4.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 09W.1)
    • Subject: Intelligent Information Systems in Production, Operation and Management (POM) (Compulsory subject)
      • Selected Topics in Intelligent Systems ( 2.0h VK / 4.0 ECTS)
        • 623.131 Selected Topics in Artificial Intelligence (2.0h VK / 4.0 ECTS)
  • Master's degree programme Information Management (SKZ: 922, Version: 05W.2)
    • Subject: Data and Knowledge Engineering (Compulsory elective)
      • Spezialgebiete des Informationsmanagements ( 4.0h VO, VK / 6.0 ECTS)
        • 623.131 Selected Topics in Artificial Intelligence (2.0h VK / 3.0 ECTS)
  • Master's degree programme Information Management (SKZ: 922, Version: 05W.2)
    • Subject: Intelligent Information Systems in Production, Operation and Management (Compulsory elective)
      • Spezialgebiete des Informationsmanagements ( 4.0h VO, VK / 6.0 ECTS)
        • 623.131 Selected Topics in Artificial Intelligence (2.0h VK / 3.0 ECTS)

Equivalent courses for counting the examination attempts

Sommersemester 2024
  • 626.017 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2023
  • 626.017 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2022
  • 626.017 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2021
  • 626.017 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2020
  • 626.017 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2019
  • 623.131 VC Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2018
  • 623.131 VC Selected Topics in Machine Learning (2.0h / 4.0ECTS)
Sommersemester 2017
  • 623.131 VC Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2016
  • 623.131 VC Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2015
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2014
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 4.0ECTS)
Sommersemester 2013
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 3.0ECTS)
Sommersemester 2011
  • 623.131 VK Selected Topics in Artificial Intelligence (2.0h / 3.0ECTS)