I857 – Computational Archaeology

Modul
Computational Archaeology
Computational Archaeology

Hinweis: Das Modul wird erstmals im Sommersemester 2025 angeboten.
Modulnummer
I857
Version: 1
Fakultät
Informatik/Mathematik
Niveau
Master
Dauer
1 Semester
Turnus
Sommersemester
Modulverantwortliche/-r

PD Prof. Dr. rer. nat. Marco Block-Berlitz
marco.block-berlitz(at)htw-dresden.de
Dozent/-in(nen)

PD Prof. Dr. rer. nat. Marco Block-Berlitz
marco.block-berlitz(at)htw-dresden.de
Lehrsprache(n)

Englisch
in "Computational Archaeology"
ECTS-Credits

5.00 Credits

Workload

150 Stunden

Lehrveranstaltungen

4.00 SWS (2.00 SWS Vorlesung | 2.00 SWS Praktikum)
Selbststudienzeit

90.00 Stunden

Prüfungsvorleistung(en)
Keine
Prüfungsleistung(en)

Schriftliche Prüfungsleistung
Modulprüfung | Prüfungsdauer: 90 min | Wichtung: 100% | wird in englischer Sprache abgenommen
in "Computational Archaeology"
Lehrform
keine Angabe
Medienform

  • Lecture materials are available as videos and the slides as PDFs
  • In addition to the lecture questionnaire, which is available at the end of each lecture, voluntary practical and theoretical exercises are offered
Lehrinhalte/Gliederung
  • Image processing
  • Pattern recognition
  • Agent-based modelling
  • Procedural generation
Qualifikationsziele

"They" will be used to shorten students in the remainder of this document to keep the objectives more compact.

  • They are able to master the necessary mathematical basics
  • They will be able to decide in a goal-oriented manner which methods of image processing will improve or prepare the data for a given problem.
  • They are able to apply simple methods of image processing.
  • They are able to apply simple pattern recognition methods to a given database.
  • They are qualified to understand agent-based models and are able to design simple simulations on their own
  • They are familiar with simple concepts of procedural generation of data
Sozial- und Selbstkompetenzen
Keine Angabe
Besondere Zulassungsvoraussetzung
Empfohlene Voraussetzungen

It is recomended to complete modul I860 Applied Mathematics and Computer Science before taking this modul.
Fortsetzungsmöglichkeiten
Literatur
  • Lambert: A Student's Guide to Bayesian Statistics, Sage Publishing, 2018
  • Zaki, Meira: Data Mining and Machine Learning: Fundamental Concepts and Algorithms, Cambridge University Press, sec. ed., 2020
  • Romanowska, Wren, Crabtree: Agent-Based Modeling for Archaeology: Simulating the Complexity of Societies, ‎ Santa Fe Institute Press, 2021
  • Shiffman: The Nature of Code: Simulating Natural Systems with Processing, The Nature of Code, 2012
Aktuelle Lehrressourcen

Script to the course und lectures notes (videos und slides as PDF)
Hinweise
Keine Angabe
Link zu Kurs/Lernressourcen im OPAL
Detailansicht schließen
© Modulux (Version 4.3)