Introduction to Machine Learning in R

Learn to build and evaluate machine-learning workflows in R with tidymodels and tidyverse. The workshop moves from problem definition, dataset splitting and preprocessing to decision trees, random forests and gradient boosting. Practical work covers cross-validation, hyperparameter tuning, regression and clustering, with model-building demonstrations, live coding, quizzes and individual or group exercises. Participants should already be comfortable with R, basic data analysis and statistics; machine-learning experience is not required.

Sessions on 8, 15, 22 and 29 January 2027, 16:00–19:30 Madrid time (CET). Fourteen live hours plus eight hours of independent exercises. Fee including VAT: EUR 546 through 31 October 2026, then EUR 610; Ambassador Institution rates EUR 436.80 and EUR 488. Limited to 15 participants. Acceptance is confirmed before payment. Delivered live online in English with practical exercises. Live attendance is required for a certificate.