Seria AAB

The general objective of the course is the consolidation and transfer of extensive knowledge regarding the main notions related to the field of predictive analysis, as a statistical method that uses specific algorithms of machine learning and data mining to predict future results based on known historical data as well as the current ones. The course presents from a theoretical point of view but is practically supported by examples with the help of specialized software applications, an introduction to the main concepts related to the field of predictive analysis:

• what are the essential steps in the predictive modeling process; - data collection; 
• statistical model formulation; 
• model evaluation; 
• analyzing the results; 
• refining the prediction model as new data is collected; 
• what are the main models used in "predictive modeling" (academic) vs. "predictive analytics" (the term for commercial predictive modeling applications); 
• the characteristics of prediction models and their suitability according to the type of application.