Ce cours apparaît dans les formations suivantes :
• IÉSEG > MSc in Big Data Analytics for Business > Semester 1 > 4,00 ECTS

Pré requis

None

Objectifs du cours

At the end of the course, the student should be able to:
- extract, manipulate, analyze and report data using R
- formulate the appropriate strategic solutions to answer to complex managerial problems
- decompose the complex problems into smaller subquestions
- look for online data sources and cutting-edge information to extract knowledge and provide the solutions
- demonstrate an expertise on key concepts, techniques and trends in the field of data analytics
- serve as a reference point for expertise-related questions in terms of data analysis
- create the solutions in a multicultural team and environment, being able to operate in a globalized environment

These competencies and/or skills contribute to the following learning objectives
- 1.B Successfully collaborate within a intercultural team
- 3.A Breakdown complex organizational problems using the appropriate methodology
- 5.B Construct expert knowledge from cutting-edge information
- 7.A Demonstrate an expertise on key concepts, techniques and trends in their professional field
- 7.B Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
- 7.D Be a reference point for expertise-related questions and ambiguities

Contenu du cours

- Run R programs in a PC environment
* Read raw input files in various formats and create R datasets
* Create new variables in the data step
* Use R procedures to describe data numerically and graphically
* Annotate R output with informative titles, labels, and formats
* Work with R datasets: sort, subset, merge, and re-format R datasets
* Use R scripts for basic statistical inference
* Create a Shiny application to create interactive reports
* Export R data and output to other computers and softwares

Modalités d'enseignement

Organisation du cours

Méthodes pédagogiques

• Coaching
• E-learning
• Interactive class
• Project work

Évaluation

- Continuous assessment using participation in the online sessions and participation in the exercises given each class. Group feedback will be given on these exercises, and personal feedback is always possible if things are not clear.
- Exam: one multiple choice mid-term exam to identify any difficulties, one programming final exam. The multiple-choice exam is corrected in class, so feedback is immediate. Personal feedback for the final exam is given after points are released on request of the student.
- Group assignment: group assignment that includes all aspects of the course. Feedback is provided per group to identify strong and weak points.

Bibliographie

• The art of R programming (Matloff, 2011) -