Advanced Data Analytics and Forecasting

• Perform an exploratory data analysis considering the following aspects: data pre-processing, calculation of sample measures, data visualization (one-dimensional and multidimensional);
• Perform dimensionality reduction for visualization purposes as well as for building statistical prediction models;
• Apply clustering methodologies to identify groups and subgroups in the data;
• Distinguish between supervised and unsupervised learning problems and, with this, identify the set of techniques/algorithms appropriate for each situation;
• Adequately apply the main machine learning techniques;
• Perform an exploratory analysis of the main sample characteristics of the time series and apply appropriate procedures in order to obtain a stationary series;
• Select the most appropriate model to the data and apply prediction methods, using the indicated software.