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.
Students with interests in analytics methods and numerical sciences may be interested to participate.
This course is designed for:
- master/Ph. D. students
- professionals engaged in data science/data analytics for business and others.
Equivalence of 3 ECTS credits
Next edition in summer 2021. Dates to be confirmed.
Applications for 2020 have closed. Final registration date for 2021 is 15th April 2021