Deep Learning Specialization on Coursera

Coursera近期新推了一个金融和机器学习的专项课程系列:Machine Learning and Reinforcement Learning in Finance Specialization(金融中的机器学习和强化学习),看起来很有意思。








· 在银行,资产管理公司或对冲基金等金融机构工作的从业人员

· 对将机器学习应用于日内交易感兴趣的个人

· 目前正在攻读金融学,统计学,计算机科学,数学,物理学,工程学或其他相关学科的学位的全日制学生,这些学生希望了解机器学习在金融领域的实际应用。


Guided Tour of Machine Learning in Finance(金融中的机器学习导览)


This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to.

Fundamentals of Machine Learning in Finance(金融中的机器学习基础知识)


The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance. A learner with some or no previous knowledge of Machine Learning (ML) will get to know main algorithms of Supervised and Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test, and implement ML algorithms in Finance. Fundamentals of Machine Learning in Finance will provide more at-depth view of supervised, unsupervised, and reinforcement learning, and end up in a project on using unsupervised learning for implementing a simple portfolio trading strategy.

Reinforcement Learning in Finance(金融中的强化学习)


This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management. Prerequisites are the courses “Guided Tour of Machine Learning in Finance” and “Fundamentals of Machine Learning in Finance”.

Overview of Advanced Methods of Reinforcement Learning in Finance(强化学习在金融中的高级方法概述)


In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high frequency trading, cryptocurrencies, peer-to-peer lending, and more.



作者 CourseEye


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