5 July 2019
R-programming for Data Science
The statistical software R has come into prominence due to its flexibility as an efficient language that builds a bridge between software development and data analysis. For example, one strength of R is the facility to develop and quickly adapt to the different needs coming from the data management and analysis community while at the same time making use of other languages in order to deliver computationally efficient solutions. The general goals of the course are:
introduce tools and workflow for reproducible research (R/RStudio, Git/GitHub, etc.);
introduce principles of tidy data and tools for data wrangling;
exploit data structures to appropriately manage data, computer memory and computations;
data manipulation through controls, instructions, and tailored functions;
develop new software tools including functions, Shiny applications, and packages;
manage software development process including version control, documentation (with embedded code), and dissemination for other users;
introduce the most recent SAS analytics tools (free access) with R and Python integration, through business related case studies.
Prof. Maria-Pia Victoria-Feser, director
Prof. Stéphane Guerrier, principal teacher
Markus Grau, SAS
Students with interests in analytics methods and numerical sciences.
This course is designed for:
master/Ph. D. students
professionals engaged in data science/data analytics for business and others.
Geneva Summer Schools will not be held responsible if the credits cannot be validated at the home institution, as it is the participant's direct responsibility to secure this approval.
CHF 1350: Final Deadline 15 April 2019
Tuition fees: CHF 1350*
External students : CHF 990*