052100 VU Algorithms and Data Structures 2 (2023S)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik

Continuous assessment of course work

Moodle

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 13.02.2023 09:00 to Th 23.02.2023 09:00
Deregistration possible until Tu 14.03.2023 23:59

Details

max. 50 participants

Language: English

Lecturers

Gramoz Goranci

Classes (iCal) - next class is marked with N

    
    Monday
    06.03.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    20.03.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    27.03.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    17.04.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    24.04.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    08.05.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    15.05.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    22.05.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    05.06.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    12.06.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    19.06.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG
    
    Monday
    26.06.
    09:45 - 11:15
    Hörsaal 2, Währinger Straße 29 2.OG
Seminarraum 6, Währinger Straße 29 1.OG

Information

Aims, contents and method of the course

This course will be taught in English and will take place on-site.

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. This course doesn’t involve any programming.

Prerequisites:
1) Discrete Mathematics – equivalent to 051110 VO Mathematical Foundations of Computer Science 1 at University of Vienna,
2) Introduction to Algorithms and Data Structures – equivalent to 051024 VU Algorithms and Data Structures 1 at University of Vienna.

Upon request, the instructor can provide additional background reading to help students fill the gaps they may have.

Content:

Algorithmic paradigms/strategies:
– Dynamic Programming
– Greedy Algorithms
Advanced Data Structures and Algorithms:
– Hashing
– Network flows

Assessment and permitted materials

Active participation is a requirement for passing the course. Each student will be asked to scribe notes for a single lecture. The overall grade will consist of the following components:

10% – scribing a single lecture
30% – two homework sets, each worth 15%
10% – two quizzes, each worth 5%
50% – final written exam

Exams/quizzes will be closed-book, closed notes, and no resources/help from the Internet will be allowed.

Minimum requirements and assessment criteria

>= 89 points, grade 1
>= 76 points, grade 2
>= 63 points, grade 3
>= 50 points, grade 4
< 50 points, grade 5

Examination topics

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

Reading list

– Algorithm Design by Jon Kleinberg and Éva Tardos.

Additional reading resources:

– Introduction to Algorithms By Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
– Algorithms by Jeff Erickson. http://algorithms.wtf/

Association in the course directory

Module: CNA

Last modified: Fr 02.06.2023 10:47