COURSES

Goals

To introduce students to research work in knowledge discovery from environmental data. Postgraduate students will acquire basic knowledge and skills about data analysis using machine learning methods. They will become acquainted with examples of the use of these methods for environmental data analysis. In the scope of practical work, they will be trained to independently use some machine learning methods for knowledge discovery from environmental data. General Competences: - The student will master selected research methods, procedures and processes - The student will develop critical thinking and self-assessment - The student will develop communication skills to present research results in an international environment - The student will be able to cooperate in a team Course Specific Competences: This course prepares students to work in this field of research.

Curriculum

Introduction to knowledge discovery and machine learning methods: - decision and regression trees, learning the rules - probability classification, nearest neighbour method, equation discovery Examples of machine learning application in environmental data analysis: - biological classification of Slovenian waters, biodegradability prediction - modelling of population dynamics and the habitats of bear, deer, etc. Practical work on environmental data using selected machine learning methods.