Introduction to Machine Learning in R (2-days workshop)

A workshop for people who are beginning their association with artificial intelligence (AI). You will be introduced to modern machine learning techniques from the ground up. Machine learning is currently used in many companies from different sectors of the economy, and the number of applications and demand for services related to it is still growing. This innovative area has applications in many fields: business, science, marketing, computer science. Every day we can observe many examples of how machine learning works: autocorrect while typing, spam filtering, gene sequence analysis, sales prediction, market research, clustering of shoppers, virtual assistants on websites. The training will be continued at the course on deep learning in R and is a live workshop with a progress check for participants and an opportunity to ask questions. Participants will receive an electronic certificate of completion after successfully passing the workshop.

Date: to be agreed with the client (2-days online workshop).

Time: 10 hours (5 hours each day with a coffee break).

Location: online.

Group: for a group larger than 3 persons.

Teacher: Tomasz Górecki, Ph.D.

Price: 380 EUR/USD (plus VAT if applicable) per person.


  • Introduction to tidyverse library – data preparation
  • Introduction to ggplot2 library – data visualization
  • Data Imputation
  • Detection of outliers
  • Coding of qualitative data
  • Linear and multiple regression
  • Collinearity of variables, nonlinear and logistic regression
  • Data dimension reduction: PCA and kernel PCA, t-SNE and UMAP methods, multidimensional scaling, correspondence analysis
  • Cluster analysis: hierarchical and non-hierarchical methods (k-means, PAM), DBSCAN method
  • Classification: nearest neighbor method, SVM, neural networks, decision trees, random forests

Tomasz Górecki, Ph.D.

Professor at the Department of Mathematical Statistics and Data Analysis at the Faculty of Mathematics and Computer Science of Adam Mickiewicz University in Poznań, Vice-Dean for grants and cooperation with business at the Faculty of Mathematics and Computer Science of Adam Mickiewicz University in Poznań. His scientific interests include time series analysis, functional data analysis and artificial intelligence. He also deals with applications of statistical methods and machine learning in practical problems. He has been teaching probability calculus, statistics, machine learning, and artificial intelligence for over twenty years. He cooperates with many companies in the field of machine learning and artificial intelligence (Lidl, OLX, PWN, Samsung, Smartstock). He has been using R language for many years (he is a co-author of two R packages and an author of a book on R language). He cooperates with employees of Colorado State University, University of Utah, Poznan University of Technology, Poznan University of Economics and Poznan University of Life Sciences.



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