This e-learning course is focused to students who are planning to work as IT specialists in the fields related to business intelligence developer, machine learning engineer, data scientist, human-centered machine learning designer, etc., who want to learn about both the practical application and implementation of machine learning methods based on one of the modern programming languages R. The aim of the course is to provide students with an in-depth introduction to two main-areas of Machine Learning: supervised and unsupervised. The course aims to cover some of the main models and algorithms for regression, classification, clustering and probabilistic classification. Topics such as regularisation, logistic and linear regression, support vector machines, neural networks, logistic and linear regression, dimensionality reduction and clustering. The course will use primarily the R Software and assumes familiarity with programming in R, probability theory and linear algebra. Software R offers many methods for implementing of the functional programming paradigm during the corresponding project creation and implementation. For these reasons, the proposed course is actual and interesting for students who are focused to development and practical implementations of IT technologies based on R language.
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