The Neural Network to teach students about machine learning techniques in economic research in a new online course
St Petersburg University launches a new online course Machine Learning Based Econometrics to teach students how to make forecasts of key socio-economic indicators and perform qualitative econometric analyses.
Students will explore the common features and key differences between the principles of statistical machine learning and traditional econometrics. They will also learn how to solve practical problems related to information sources and processing potentially large amounts of data.
You can sign up for the course here.
The online course will also cover what programming languages and digital libraries are necessary to work effectively with computer systems and artificial intelligence. In addition, students will be able to explore elements of machine learning such as neural networks, random forests, and parallel algorithms. The course also provides an opportunity to put this knowledge into practice by completing exercises that involve real data and Python codes.
The programme comprises four main modules. The first two introduce students to the basic concepts and algorithms of machine learning. The third module explores the impact of big data processing on the quality of analyses of econometric studies. In the fourth module of the course, students get the opportunity to put the acquired knowledge into practice through working on their own project in the field of econometrics.
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In the new online course, for the first time, the lecturer is a digital avatar created with the help of a neural network. The educational materials for the virtual lecturer have been carefully prepared by experts from the international team of the Centre for Econometrics and Business Analytics of St Petersburg University.
The course is theoretical and practical and is delivered in English.