https://at-ceu.studyguide.timeedit.net/modules/ECBS5171?type=COREData Analysis 3 covers the fundamentals of data analysis with the aim of prediction also called predictive analytics. This course equips students with the knowledge and skills necessary to carry out and evaluate predictions in business and policy environments. Similar to Data Analysis 2 we focus on select few applications, those that offer good performance and are widely used in industry. This course starts with the fundamentals of predictive analytics and covers topics such as prediction from regressions, tree-based models (regression and classification trees to random forest and GBM), as well as a variety of time series forecasting models. We often compare variety of prediction models in terms of predictive performance, speed and interpretability. We discuss model independent issues such as sample design and external validity of the results. Seminars will use Python. Seminars will focus on case studies and the process of developing projects with and without AI. ?In business applications, prediction is an essential part of data analysis. More and more often, prediction is used in policy analysis as well. Machine learning applications have also become prevalent in both industry and policy, understanding how algorithms work is a crucial new skill.