Inhalt

[ 536COSCAD1V19 ] VL (*)Algorithms and Data Structures 1

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
3 ECTS B1 - Bachelor 1. Jahr Artificial Intelligence Alois Ferscha 2 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Bachelorstudium Artificial Intelligence 2025W
Lernergebnisse
Kompetenzen
(*)Students are able to think algorithmically and analyze the efficiency of algorithms and data structures.
Fertigkeiten Kenntnisse
(*)
  • Understand and implement basic static and dynamic data structures such as lists, stacks, and queues. (K2, K3)
  • Apply recursion and backtracking in algorithmic solutions. (K3)
  • Utilize sorting and search algorithms, including advanced techniques like digital sorting. (K3)
  • Analyze algorithm complexity, focusing on runtime and memory usage. (K4)
  • Work with trees, heaps, and priority queues in problem-solving. (K3)
  • Incorporate random numbers and use randomized algorithms. (K3)
  • Work with strings and pattern matching algorithms. (K3)
  • Develop solutions in Python and efficiently use its data structures and libraries. (K6)
(*)The course covers the following topics:

  • Complexity
  • Lists, Stacks, Queues
  • Recursion
  • Backtracking
  • Trees
  • Heaps, Priority Queues
  • Sorting (including digital sorting)
  • Strings and Patterns
  • Random Numbers
  • Randomized Algorithms
Beurteilungskriterien (*)Exam at the end of term
Lehrmethoden (*)Slide-based presentation
Abhaltungssprache Englisch
Literatur (*)Slides will be available in the course section in moodle. Additional literature will be announced in the course.
Lehrinhalte wechselnd? Nein
Sonstige Informationen (*)This lecture and the corresponding lab form an inseparable didactic unit. The learning outcomes described here are achieved through the interaction of the two courses.
Präsenzlehrveranstaltung
Teilungsziffer -
Zuteilungsverfahren Direktzuteilung