262014 VU Algorithms and Data Structures for Computational Science (2024S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 05.02.2024 08:00 bis Di 27.02.2024 07:00
- Abmeldung bis Fr 22.03.2024 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
UPDATE: Note that this course will only start on Thursday, March 7.
There will be two classes per week in the first semester half (until the midterm exam) and *on average* one class per week in the second semester half (after the midterm exam).Please check on Moodle for the exact dates in the second semester half!
Donnerstag
07.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Donnerstag
14.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
19.03.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
21.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Donnerstag
11.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
16.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
18.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
23.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
25.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
30.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
02.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
07.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Dienstag
14.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
16.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
21.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
N
Donnerstag
23.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
28.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Dienstag
04.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
06.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
11.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
13.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Dienstag
18.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Donnerstag
20.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
A total of 100 regular points (100%) can be reached.The number of lectures will be divided into two roughly equally-sized sections. In each of the two sections, there will be
- 1 written exam (90 minutes) for up to 40 regular points,
- 2 homework sheets with several small problems each, one of them needs to be presented in class for up to 10 regular points,
resulting in 2 * (40 + 10) = 100 regular points.
No materials are allowed for the written exams.Up to 25 bonus points can be reached:
- 5 bonus points if you miss at most 2 classes (-1 for every further missed class)
- up to 5 bonus points per semester half (= 2*5 in total) for solving one of the extra problems on a homework sheet
- x <= 2.5 bonus points per homework sheet (= 4*2.5 in total) for readiness to present >= x+1 problems on that sheet in classPreliminary dates for the exams:
midterm exam: April 30, 2024
final exam: June 18, 2024
- 1 written exam (90 minutes) for up to 40 regular points,
- 2 homework sheets with several small problems each, one of them needs to be presented in class for up to 10 regular points,
resulting in 2 * (40 + 10) = 100 regular points.
No materials are allowed for the written exams.Up to 25 bonus points can be reached:
- 5 bonus points if you miss at most 2 classes (-1 for every further missed class)
- up to 5 bonus points per semester half (= 2*5 in total) for solving one of the extra problems on a homework sheet
- x <= 2.5 bonus points per homework sheet (= 4*2.5 in total) for readiness to present >= x+1 problems on that sheet in classPreliminary dates for the exams:
midterm exam: April 30, 2024
final exam: June 18, 2024
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.
If you fail to show up for an exam, you will receive 0 points for this exam.Homework sheets must be submitted before the deadline to be eligible for presentation in class. You can indicate for each problem on a homework sheet whether you would be willing to present it. The presenter for each problem is chosen by the instructors among all those that are willing to present, with ties broken randomly. There will be enough problems so that each student can present twice if everyone is willing to present all problems. If you fail to submit a homework sheet or are not chosen for presentation because you were unwilling to present many of the subproblems or are chosen to present but don't show up, you will receive 0 points.
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.
If you fail to show up for an exam, you will receive 0 points for this exam.Homework sheets must be submitted before the deadline to be eligible for presentation in class. You can indicate for each problem on a homework sheet whether you would be willing to present it. The presenter for each problem is chosen by the instructors among all those that are willing to present, with ties broken randomly. There will be enough problems so that each student can present twice if everyone is willing to present all problems. If you fail to submit a homework sheet or are not chosen for presentation because you were unwilling to present many of the subproblems or are chosen to present but don't show up, you will receive 0 points.
Prüfungsstoff
- all material presented and discussed in class
- contents and discussion of all exercise sheets
- reading material as provided on Moodle
- contents and discussion of all exercise sheets
- reading material as provided on Moodle
Literatur
Literature will be announced in class and (as far as possible) made available on Moodle.
Zuordnung im Vorlesungsverzeichnis
PM-ADS
Letzte Änderung: Mi 20.03.2024 07:46
- design and analysis of algorithms especially for graph and clustering problems
- efficient exact and approximation algorithms for optimization problems (greedy algorithms, Linear Programming)
- algorithms for big data (online algorithms, streaming algorithms, external memory algorithms)On successful completion of this course, you will be familiar with the above concepts and methods and able to use them on your own in practice.The schedule consists of interactive lectures as well as homework presentations and discussions.Students are expected to have acquired basic knowledge in algorithms and data structures, e.g. 051024 VU Algorithms and Data Structures 1, prior to taking this course. See also the Extension Curriculum Basic Knowledge in Computational Sciences.If you are unsure whether you meet these prerequirements, please contact the lecturer(s).