From data to decision - applied machine learning in R or Python


The training aims to introduce R or Python language in terms of data science issues. Its scope summarizes the basic path of machine learning process and working with data.


It is intended for people with at least intermediate programming level and knowledge of the basics of statistics. The plan could be fitted to the particular needs.


  1. Introduction to R (day 1)
    • RStudio IDE
    • Data types
    • Operations on vectors, matrices and lists
    • Programming syntax
    • Data frames
    • External packages
    • Loading and saving data
    • Introduction to statistics
  2. Data preparation, visualization and analysis techniques (day 2)
    • Data preparation, manipulation and cleaning
    • Data visualization (base package, ggplot2, interactive extensions, maps)
    • Linear, logistic, generalized models, ANOVA
    • Time and dates in R
    • Time series analysis, modeling and predicting
  3. Machine Learning and predictive models I (day 3)
    • Naive Bayes
    • Recursive Partitioning
    • Bagging (e.g., random forests)
    • Boosting (e.g., GBM)
    • Support Vector Machines (SVM)
    • Clustering/KNN
  4. Machine Learning and predictive models II (day 4)
    • Factor Analysis (FA)
    • Principal Component Analysis (PCA)
    • Dimensionality reduction
    • Ensemble models
    • Artificial neural networks (pattern recognition / clustering / time series analysis/ model fitting)
    • Hidden Markov Models (HMM)
    • Introduction to Natural Language Processing
  5. Introduction to Big Data / Automated reporting / Shiny package (day 5)
    • External API
    • Overview of Apache projects
    • Sample datasets analysis
    • Automated and interactive reporting
    • Shiny package

Meet the trainer


Has background in Machine Learning, Deep Learning, Natural Language Processing, Signal Processing and Time Series Modeling and Forecasting. Cheerful, creative and calm person, who is business- and scientific-oriented, experienced in providing outdoor trainings and conducting biomedical applications. Holds a MSc degree in Biomedical Engineering from Warsaw University of Technology.

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From data to decision - applied machine learning in R or Python

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