Learning outcomes

At the end of this course, the student should be able to:
• Use basic and advanced functions in the R software to process a dataset from its import to the export of advanced graphics;
• Write an operational script to apply advanced data import, manipulation and analysis functions with the R language;
• Appropriately use vocabulary relating to computer science concepts and, in particular, the R language.
• Create documents in Rmarkdown.

Goals

The objective of the course is to provide the tools for future scientists to import, manipulate and analyse datasets using R software. In this context, different skills to be acquired have been defined. 

Content

The student acquires the skills covered by the course by completing a project that serves as the basis for the course assessment. Throughout the project, the student is required to answer a series of specially constructed questions in order to exercise these skills. An example of a project is presented in the theory course and is used to teach the students how R works and the basic principles of programming. The project is carried out by the students during the practical sessions, in particular. During these sessions, students work on their project independently and can ask the assistants for help. The progress of the student in his project and the mastery of the concepts and tools necessary to carry it out are evaluated at the end of the practical work (see Evaluation). In addition, the final version of the project is submitted by the students to the teacher at the end of the term. An oral examination, in session, completes the student's grade (see Assessment). The course is structured around the following points: • Reminder of basic functions in R • Main steps in processing a dataset • Use of advanced functions • Tips for improving the presentation of results • Tips for building good charts and tables in R • Examples of application  • Solving exercises independently

Teaching methods

A large part of the face-to-face course (auditorium hours and practical work) takes place at the beginning of the term. The student is expected to work on his/her own for the rest of the term. The theory course is divided into five parts: • A brief introduction to the value of computer tools and programming in the scientific process; • An example of processing a dataset step by step;  • A deepening of the principles related to the description and representation of scientific data. During the practical work, the student is required to use the basic functions of the R software but also to learn new ones. To do this, they must consult the course, the software's help sections and the online resources (tutorials, courses, forums, etc.). 

Assessment method

Continuous assessment (no second session). A test at the end of each practical work (40%) and a project (60%). The project is defended orally at the end of the term.
The project is made up of 4 parts, each the focus of a practical work. Students must complete their project alone. The project html should show all final responses.

Language of instruction

French
Training Study programme Block Credits Mandatory
Bachelor in Veterinary Medicine Standard 0 2
Bachelor in Geography : General Standard 0 2
Bachelor in Biology Standard 0 2
Bachelor in Geology Standard 0 2
Bachelor in Veterinary Medicine Standard 2 2
Bachelor in Geography : General Standard 2 2
Bachelor in Biology Standard 2 2
Bachelor in Geology Standard 2 2