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Teaching Note—Data Science Training for Finance and Risk Analysis
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Orientador(es)
Resumo(s)
The main discussion of this paper is a method of data science training, which allows responding to the complex challenges of finance and risk analysis. There is growing recognition of the importance of creating and deploying financial models for risk management, incorporating new data and Big Data sources. Automating, analyzing, and optimizing a set of complex financial systems requires a wide range of skills and competencies that are rarely taught in typical finance and econometrics courses. Adopting these technologies for financial problems necessitates new skills and knowledge about processes, quality assurance frameworks, technologies, security needs, privacy, and legal issues. This paper discusses a pedagogical approach to overcome the teaching complexity of needed soft and hard skills in an integrated manner with its advantages, disadvantages, and vulnerabilities.
Descrição
Ashofteh, A. (2023). Teaching Note—Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms. In C. P. Kitsos, T. A. Oliveira, F. Pierri, & M. Restaino (Eds.), Statistical Modelling and Risk Analysis: Selected contributions from ICRA9, Perugia, Italy, May 25-27, 2022 (Vol. 430, pp. 17-25). (Springer Proceedings in Mathematics & Statistics). Springer Nature. https://doi.org/10.1007/978-3-031-39864-3_2
Palavras-chave
Data Science Finance Risk Analysis Active Learning Big Data General Mathematics SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth SDG 9 - Industry, Innovation, and Infrastructure SDG 10 - Reduced Inequalities
Contexto Educativo
Citação
Editora
Springer Nature