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Data Analysis

Full course description

Data Analysis is a scientific discipline that deals with the processes of inspecting, cleaning transforming, and modeling data. The final goal of data analysis is to derive information and knowledge that can be used for further decision making. This course covers two major subfields of data analysis: data mining and signal processing. For both subfields a number of key techniques will be discussed. Examples of such techniques are, among others, Fourier analysis, wavelet analysis, ensemble learning and clustering. The course lectures will be accompanied by practical labs in which the students will apply analysis techniques to data from various sources. After completing this course students will be able to judge the quality of data-mining and signal analysis processes, results and tools. Students will be able to apply the knowledge and insight obtained in this course whenever data needs to be analyzed.analysis processes to specialists or non-specialists. Skills: After successful completion of the course students will be able to analyze data using data-mining and time-series analysis techniques, and to design and implement data-mining and signal processing algorithms and tools. Study Material: to be announced





study/bachelor/year_3/block_4/data_analysis.txt · Last modified: 2020/11/14 22:49 (external edit)