Machine Learning and Graduate Education in Finance

This paper discusses the application of machine learning in graduate education in finance, emphasizing its importance in data analysis, prediction, and causal inference. The paper points out that machine learning can enhance students' professional competence, expand their knowledge areas, and enhance their work abilities. Through theoretical teaching and research applications, machine learning methods can help process large amounts of unstructured data and combine with traditional econometric methods to improve the accuracy and explanatory power of research. The survey results support the effectiveness of machine learning teaching. At the end of the paper, it is proposed to continuously update the teaching content of machine learning technology, while paying attention to its limitations, in order to promote the improvement of students' comprehensive abilities.