Universität Wien

052100 VU Algorithms and Data Structures 2 (2025S)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Prüfungsimmanente Lehrveranstaltung
Moodle
Mo 28.04. 09:45-11:15 Hörsaal 2, Währinger Straße 29 2.OG

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

The link to attend the kickoff meeting on March 3rd will be sent out in time to all registered students.

Please note that attendance is *mandatory*. By study law, students that do not attend have to be deregistered/lose their spot on the waiting list.

  • Montag 03.03. 09:45 - 11:15 Digital
  • Montag 10.03. 09:45 - 11:15 Hörsaal A UniCampus Zugang Hof 2 2F-EG-32
  • Montag 17.03. 09:45 - 11:15 Hörsaal A UniCampus Zugang Hof 2 2F-EG-32
  • Montag 24.03. 09:45 - 11:15 Hörsaal A UniCampus Zugang Hof 2 2F-EG-32
  • Montag 31.03. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 07.04. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 05.05. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 12.05. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 19.05. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 26.05. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 02.06. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 16.06. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 23.06. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
  • Montag 30.06. 09:45 - 11:15 Hörsaal 2, Währinger Straße 29 2.OG
    Seminarraum 3, Währinger Straße 29 1.UG
    Seminarraum 8, Währinger Straße 29 1.OG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

**Please note: The course is fully booked. We therefore cannot take any late registrations, unfortunately.**

The main objective of this course is to learn some of the key techniques for designing and analyzing algorithms. We will study algorithmic paradigms and show concrete examples on how to use these paradigms to solve different optimization problems. This is a theoretical course, and we’ll largely be focusing on using mathematical tools to prove the correctness and the running time complexity of the algorithms.

At the end of the course, you should be able to recognize which paradigm you would need to use for solving new problems, as well as study the correctness and the time complexity of your suggested solutions.

Prerequisites:
- Discrete Mathematics – equivalent to 051110 VO Mathematical Foundations of Computer Science 1
- Introduction to Algorithms and Data Structures – equivalent to 051024 VU Algorithms and Data Structures 1

Topics:

* Proof Techniques

* Algorithmic Strategies:
- Dynamic Programming
- Greedy Algorithms

* Data Structures and Algorithms
- Maximum Flow
- Shortest Paths
- Hashing

Please note: The cluster Algorithms has two gatekeepers, this course *and* VU Numerical Algorithms, 3 ECTS. Both are required.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students can collect up to 101 regular points as follows:
- 2 online multiple choice quizzes (up to 10 points each)
- 2 homework sheets (up to 15 points each)
- 11 questions of the day (up to 11 points)
- written exam (up to 40 points)

In addition, up to 20 bonus points can be collected as follows:
- attending >= 12 classes (up to 5 points)
- prerequisites quiz (up to 5 points)
- solving bonus problems on homework sheets (up to 10 points)

Exams/quizzes are closed-book, no resources/help from the Internet are allowed.

Mindestanforderungen und Beurteilungsmaßstab

If P is the sum of regular and bonus points received, your grade will be:

1, if P >= 89,
2, if P >= 76,
3, if P >= 63,
4, if P >= 50,
5, otherwise.

Presence is mandatory for the first lecture. Otherwise, it is not a requirement, but strongly recommended.
There is no minimum required number of points per exam/homework sheet/quiz.

Prüfungsstoff

Everything covered in the lecture, the reading material, the homework problems, and the quizzes.

Literatur

- Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford. Introduction to Algorithms. MIT Press, 2009/2022 (3rd & 4th edition).
- Kleinberg, Jon; Tardos, Éva. Algorithm Design. Pearson, 2006.
- Erickson, Jeff. Algorithms. Online resource: http://algorithms.wtf/

Further literature will be provided via Moodle.

Zuordnung im Vorlesungsverzeichnis

Module: CNA

Letzte Änderung: So 02.03.2025 12:45