The volume of data worldwide is growing daily and potential business value lay in the data. Looking for new business opportunities in data today is an essential part of the growth of business in any sector. Knowledge discovery from data is a helical process that includes data retrieval, data pre-processing, selection and application of appropriate analytical methods, and interpretation of results. Data mining is the use of statistical and machine-learning techniques on historical data aiming to obtain an explanation or prediction. The course deals with key data mining approaches from supervised and unsupervised learning – regression, classification, clustering and association rules mining - by introducing the most popular methods in each of them. The need and opportunities for analytics arise in variaty of tasks., e,g, sensor data processing, social network analysis, customer relationship etc. Text mining and dealing with unstructured and semi-structured data is one of the topical classification targets. The course focuses on compreheanson and practice, using freeware tool Weka (additionally - Python language for experienced users) to analyse real data sets and interpret the insights. Students work in teams and apply their knowledge and skills in data analysis to develop a capstone project.