(*) Unfortunately this information is not available in english.
Workload
Education level
Study areas
Responsible person
Hours per week
Coordinating university
3 ECTS
B2 - Bachelor's programme 2. year
Computer Science
Alois Ferscha
2 hpw
Johannes Kepler University Linz
Detailed information
Original study plan
Bachelor's programme Computer Science 2025W
Learning Outcomes
Competences
Students are able to apply advanced algorithms and data structures, to solve complex problems.
Skills
Knowledge
Students
understand and can implement advanced search techniques using trees and hashing methods. (K2, K3)
can work with graphs, can implement them and can analyze structural properties and interaction patterns.(K3)
can utilize advanced graph algorithms for tasks like analyzing social graphs and understanding network dynamics. (K3)
can apply optimization techniques using evolutionary algorithms and PRAM (Parallel Random Access Machine) algorithms. (K3)
can develop solutions tailored to specific problems by leveraging and combining known algorithms. (K6)
can analyze social and document graphs to study patterns such as power laws and epidemic spread. (K4)
The course covers the following topics:
Randomized Algorithms
Search Trees
Hashing
Distributed Hashing
Graphs
Social Graphs
Power Law/Epidemic Spread
Evolutionary Algorithms
Document Graphs
PRAM Algorithms
Criteria for evaluation
Exam at the end of term
Methods
Slide-based presentation
Language
English and French
Study material
Slides will be available in the course section in Moodle. Additional literature will be announced in the course.
Changing subject?
No
Further information
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. The lecture is independent of programming languages. Labs are offered in Java and Python.
Corresponding lecture
(*)INBPDVOALG2: VO Algorithmen und Datenstrukturen 2 (3 ECTS)
