ECTS
2 credits
Training Structure
College of Sciences
Description
This R programming course is intended for students who, in their professional practice, will need to know a programming language to perform advanced data processing. The goal is therefore to learn how to properly structure, comment on, and debug code. This course is intended for both M1 SSD and M1 Bio-Info students. It is not intended to treat packages as “black boxes” for implementing statistical methods.
Objectives
Master the basic syntax of the R language for scientific programming.
Class Hours
- R Programming - TutorialTutorials12 hours
- R Programming - LectureLecture6 hours
Mandatory Prerequisites
L3 Science
Recommended prerequisites: some basic knowledge of statistics and probability. Knowledge of a programming language would be a plus.
Knowledge Assessment
Comprehensive Ongoing Monitoring by Project
Course Outline
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 Practices of Debugging.
5) Version Control
6) Documentation
7) Integrated Development Environments.
Additional Information
Hours:
Lectures: 6 hours
Tutorials: 10.5 hours
Lab sessions:
Fieldwork: