- Level Professional
- المدة
- الطبع بواسطة New York University
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Offered by
عن
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.Auto Summary
Explore "Machine Learning and Reinforcement Learning in Finance," a professional-level course by Coursera focusing on applying ML algorithms to financial problems. This course is ideal for finance practitioners, day traders, and students in related fields. With flexible subscription options, it aims to equip learners with practical skills to map, choose, and implement ML solutions in finance. Perfect for enhancing your expertise in the intersection of technology and finance.

Instructor
Igor Halperin