Reproducible Research
Informacje ogólne
Kod przedmiotu: | 2400-DS2RR | Kod Erasmus / ISCED: |
14.3
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Nazwa przedmiotu: | Reproducible Research | ||
Jednostka: | Wydział Nauk Ekonomicznych | ||
Grupy: |
Anglojęzyczna oferta zajęć WNE UW Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 1 (6*30h) Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 2 (2*30h) Przedmioty obowiązkowe dla II roku Data Science and Business Analytics |
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Punkty ECTS i inne: |
4.00 ![]() |
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Język prowadzenia: | angielski | ||
Rodzaj przedmiotu: | obowiązkowe |
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Skrócony opis: |
The main objective of the course is to present the key concepts of the research reproducibility, its importance in scientific and commercial R&D processes, and to provide students with the basic practical knowledge of a few most popular in the industry modern reproducibility tools. |
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Pełny opis: |
The course consists of computer labs; each class will be split into theoretical and practical part. The following topics will be discussed (not necessarily in the presented order): 1. Introduction • Importance of reproducibility in the R&D process • Consequences of lack of reproducibility • Best practices 2. Reporting tools • Introduction to RMarkdown and RBookdown • Best programming practices 3. Networking & Security • Introduction to linux shell • Network security on the example of public/private key pairs • Connecting to remote computers 4. Version control systems • Introduction to git • Worst & best practices with git • Practical remarks 5. Remote repositories & Utility tools • Introduction to github • Basics of project workflow • Project management tools 6. Cloud environment • Introduction to Amazon Web Services • Cloud deployment 7. Summary and outlook |
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Literatura: |
Lecture slides Numerous online resources |
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Efekty uczenia się: |
Upon the completion of the course, student: 1. understands the general concept of research reproducibility; knows the reproducibility tools classification; understands which tool can be used in a given context; 2. has basic skills in computer tools allowing to achieve research reproducibility and replicability; has basic skills in modern best programming practices; has basic skills in the cloud development environment; is able to employ skills gained during the course while participating in modern scientific and commercial data science projects; 3. is aware of the importance of reproducibility in data science, as well as in science and development in general; is aware that reproducibility tools are evolving rapidly and that constant training in this area is required to keep skills up to date; is aware of the trends in modern data science and IT development; K_W01, K_U01, K_U02, K_U03, K_U04, K_U05, KS_01, K_U06 |
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Metody i kryteria oceniania: |
1. Presence on the classes 2. Up to three homework projects |
Zajęcia w cyklu "Semestr letni 2021/22" (w trakcie)
Okres: | 2022-02-21 - 2022-06-15 |
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Typ zajęć: |
Konwersatorium, 30 godzin ![]() |
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Koordynatorzy: | Wojciech Hardy, Łukasz Nawaro | |
Prowadzący grup: | Wojciech Hardy, Łukasz Nawaro | |
Lista studentów: | (nie masz dostępu) | |
Zaliczenie: |
Przedmiot -
Egzamin
Konwersatorium - Egzamin |
Właścicielem praw autorskich jest Uniwersytet Warszawski.