Study programme 2022-2023 | Français | ||
Data Sciences IV : reproducible research | |||
Programme component of Master's in Biology of Organisms and Ecology : Research Focus (MONS) (day schedule) à la Faculty of Science |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
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US-M2-BIOEFA-015-M | Optional UE | GROSJEAN Philippe | S807 - Ecologie numérique |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
---|---|---|---|---|---|---|---|---|---|
| Français | 0 | 30 | 0 | 0 | 0 | 3 | 3.00 | 1st term |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
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S-BIOG-077 | Data Sciences IV : reproducible research | 0 | 30 | 0 | 0 | 0 | Q1 | 100.00% |
Programme component |
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Objectives of Programme's Learning Outcomes
Learning Outcomes of UE
To specialize students in biology in biological data science through their initiation to various complementary concepts to previous courses. This course supplements data science concepts taught until now with various more advanced topics: floating-point calculation precision, best coding of data in relation with the current problem, how to realize perfectly reproducible analyses, reproducible pseudo-random generators, writing functions and objects. This course is partly modular in function of specific needs of students.
UE Content: description and pedagogical relevance
The pedagogical material is available online: https://wp.sciviews.org. The chapters of this UE are (can possibly change according to the needs of the students that take this UE):
- Particular data: dates, text, circular variables
- Projects: structure, different types of reproducible documents
- Code modularization: functions, documentation
- Code optimisation: tests, objects, optimisation techniques
- Initiation to packages and continue integration
- Parallelization and cloud computing
Prior Experience
General knowledge in data science, including project management, data importation and transformation, visualization of data through graphs and bases of writing reproducible reports. Advanced biostatistics in main areas used in biological data analyses.
An update of knowledge prior to the course can be done via material related to courses 1 to 3 in data science available online at https://wp.sciviews.org.
Type of Teaching Activity/Activities
AA | Type of Teaching Activity/Activities |
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S-BIOG-077 |
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Mode of delivery
AA | Mode of delivery |
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S-BIOG-077 |
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Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
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S-BIOG-077 | The content for this course is available online https://wp.sciviews.org |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
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S-BIOG-077 | Not applicable |
Other Recommended Reading
AA | Other Recommended Reading |
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S-BIOG-077 | Barnier, J., 2018. Introduction à R et au tidyverse (https://juba.github.io/tidyverse/index.html). Ismay, Ch. & Kim A.Y, 2018. Moderndive: An introduction to statistical and data science via R (http://moderndive.com). Wickham, H. & Grolemund, G, 2017. R for data science (http://r4ds.had.co.nz). Chambers, J.M., 2008. Software for data analysis. Programming with R. Springer, New York, 498pp. Dagnelie, P., 2007. Chambers, J.M., 1998. Programming with data. A guide to the S language. Springer, New York, 469pp. Fortner, B., 1995. The data handbook. A guide to understanding the organization and visualization of technical data. Springer, New York, 350pp. |
Grade Deferrals of AAs from one year to the next
AA | Grade Deferrals of AAs from one year to the next |
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S-BIOG-077 | Authorized |
Term 1 Assessment - type
AA | Type(s) and mode(s) of Q1 assessment |
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S-BIOG-077 |
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Term 1 Assessment - comments
AA | Term 1 Assessment - comments |
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S-BIOG-077 | Evaluation based on a report that applies the techniques stidued in this course, as well as the different exercices done in the modules.. |
Resit Assessment - Term 1 (B1BA1) - type
AA | Type(s) and mode(s) of Q1 resit assessment (BAB1) |
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S-BIOG-077 |
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Term 3 Assessment - type
AA | Type(s) and mode(s) of Q3 assessment |
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S-BIOG-077 |
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Term 3 Assessment - comments
AA | Term 3 Assessment - comments |
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S-BIOG-077 | Similar to Q1. |