262014 VU Algorithms and Data Structures for Computational Science (2024S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 05.02.2024 08:00 to Tu 27.02.2024 07:00
- Deregistration possible until Fr 22.03.2024 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
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!
Thursday
07.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Thursday
14.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
19.03.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
21.03.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Thursday
11.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
16.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
18.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
23.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
25.04.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
30.04.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
02.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
N
Tuesday
07.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Tuesday
14.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
16.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
21.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
23.05.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
28.05.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Tuesday
04.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
06.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
11.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
13.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Tuesday
18.06.
15:00 - 16:30
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
20.06.
15:00 - 16:30
Seminarraum 15, Kolingasse 14-16, OG01
Information
Aims, contents and method of the course
Assessment and permitted materials
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
Minimum requirements and assessment criteria
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.
Examination topics
- 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
Reading list
Literature will be announced in class and (as far as possible) made available on Moodle.
Association in the course directory
PM-ADS
Last modified: We 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).