ECTS
2 credits
Training structure
Faculty of Science
Description
This R programming course is intended for students who will need to know a programming language for advanced data processing in their professional practice. The aim is therefore to learn how to structure, comment, and debug code properly. This course is intended for both M1 SSD and M1 Bio-Info students. It is not intended for the use of packages as black boxes for the implementation of statistical methods.
Objectives
Master the basic syntax of the R language for scientific programming.
Teaching hours
- R Programming - TutorialTutorials12 p.m.
- R Programming - CMLecture6 hours
Mandatory prerequisites
L3 scientific
Recommended prerequisites: some knowledge of statistics and probability. Knowledge of a programming language would be a plus.
Knowledge assessment
Full continuous assessment by project
Syllabus
1) Importing/Exporting data
2) Graphics
3) Programming:
- algorithms, modules, tests.
- variables, vectors, arrays, lists.
- functions, conditions, loops.
- objects
- interpretation & compilation
- dynamic libraries
4) Principles and practice of debugging.
5) Version management
6) Documentation
7) Integrated development environments.
Additional information
Hours per week:
Lectures: 6 hours
Tutorials: 10.5 hours
Practical work:
Fieldwork: