 | Study programme 2019-2020 | Français | |
| Data Sciences IV: practice | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| S-BIOG-043 |
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| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 0 | 0 | 0 | 0 | 20 | A |
| Organisational online arrangements for the end of Q3 2019-2020 assessments (Covid-19) |
|---|
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| Description of the modifications to the Q3 2019-2020 online assessment procedures (Covid-19) |
| The report of the analyses within a Github Classroom repository will be evaluated. |
Content of Learning Activity
The chapters of this AA are :
- Practice I, multi-file templates
- Data I - Dates, circular data, ...
- Data II - Text & regular expressions
- Practice II, modularization & functions
- Practice III, open data
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
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). Zar, J.H., 2010. Biostatistical analysis (5th ed.). Pearson Education, London. 944pp. Dagnelie, P., 2007. Statistique théorique et appliquée, Volumes I et II (2ème ed.). De Boeck & Larcier, Bruxelles. 511pp (vol. I) 734pp (vol. II).
Mode of delivery
- Face to face
- Mixed
Type of Teaching Activity/Activities
- Excursions, visites
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)