Algorithmics
General data
Course ID: | 1000-2D97AL |
Erasmus code / ISCED: |
11.304
|
Course title: | Algorithmics |
Name in Polish: | Algorytmika |
Organizational unit: | Faculty of Mathematics, Informatics, and Mechanics |
Course groups: |
Master seminars for Computer Science MSc seminars for Machine Learning |
ECTS credit allocation (and other scores): |
6.00
|
Language: | English |
Type of course: | elective seminars |
Short description: |
In this seminar we study algorithms for discrete problems and data structures. We discuss methods of designing algorithms for discrete problems and analyzing their time complexity. We are interested in classical sequential algorithms as well as parallel, distributed, randomized and approximation algorithms. Efficient data structures are also studied. |
Full description: |
In this seminar we study algorithms for discrete problems. We discuss methods of designing such algorithms and analyzing their time complexity. We are interested in classical sequential algorithms as well as parallel, distributed, randomized and approximation algorithms. Efficient data structures are also studied. During the seminar students present articles from scientific journals and proceedings of conferences devoted to the area of algorithms and data structures. Possible kinds of MSc theses include original research, experiments, surveys and implementations of computer systems with non-trivial algorithmic elements. The classes may be in English in case foreign students are present. |
Bibliography: |
Modern scientific literature of the subject, including scientific journals and data from Internet. Details are provided by the lecturers at the first meeting. |
Learning outcomes: |
Knowledge (KW_01, KW_02): The student knows the basic algorithms and algorithmic techniques and data structures, understands the current "trends" in this field, in particular, he knows: 1. Graph algorithms. 2. Text algorithms. 3. Approximation algorithms. 4. Exact exponential Algorithms. 5. Parallel algorithms Skills (K_U01, K_U02, K_U04, K_U05, K_U11 - KU_15): The student can specify algorithmic problems, is able to analyze the problem and propose an efficient solution. The student is able to write scientific publication in the field of algorithms, also in English. The student is able to prepare a presentation in the field of algorithms, also in English. Social competence (K_K01-K_K09): The student is able to find the information on the given research problem in available sources and evalutes its reliability and usefulness. The student can present specialized results in a manner understandable to non-specialists. The student understands the importance of intellectual property rights in the use of other people's results. |
Assessment methods and assessment criteria: |
Active participation in the seminar and giving a talk. |
Classes in period "Academic year 2023/24" (in progress)
Time span: | 2023-10-01 - 2024-06-16 |
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MO TU W TH SEM-MGR
FR |
Type of class: |
Second cycle diploma seminar, 60 hours
|
|
Coordinators: | Adam Karczmarz, Michał Pilipczuk, Jakub Radoszewski | |
Group instructors: | Adam Karczmarz, Marcin Pilipczuk, Jakub Radoszewski | |
Students list: | (inaccessible to you) | |
Examination: | Pass/fail |
Classes in period "Academic year 2024/25" (future)
Time span: | 2024-10-01 - 2025-06-08 |
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MO TU W TH FR |
Type of class: |
Second cycle diploma seminar, 60 hours
|
|
Coordinators: | Adam Karczmarz, Michał Pilipczuk, Jakub Radoszewski | |
Group instructors: | Adam Karczmarz, Marcin Pilipczuk, Jakub Radoszewski | |
Students list: | (inaccessible to you) | |
Examination: | Pass/fail |
Copyright by University of Warsaw.