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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/machine-learning-investment
课程评论：没有评论
课程名称：投资专业人士的机器学习 概述：此课程专为投资专业人士或具备投资行业知识的人员量身定制，旨在帮助他们培养机器学习技术的基本实用理解，以及这些技术在投资过程中的应用。课程结合真实案例，涵盖投资专业人士保持竞争力所需的技术性与“软技能”。 您将在课程中学习到： - 区分监督学习与非监督学习和深度学习 - 描述机器学习算法性能的评估方式 - 描述监督学习与非监督学习算法，并确定它们适合解决的问题 - 描述神经网络、深度学习网络和增强学习 - 选择合适的机器学习算法 - 描述将机器学习与数据项目集成的价值 - 与数据科学家和投资团队合作，从大型和另类数据集中提取信息和见解 - 将CFA协会伦理决策框架应用于机器学习的道德困境 该课程是CFA协会提供的数据科学为投资专业人士专业化的一部分。 课程大纲： 1. 部分：机器学习 2. 部分：监督学习 3. 部分：非监督学习 4. 部分：深度学习 5. 部分：翻译者 6. 部分：最终项目 描述：这是一个实践机会，让您应用在本课程中学习到的知识，为投资团队和数据科学团队之间的“翻译者”角色做好准备。该项目旨在指导您通过投资专业人士在机器学习方法应用中可能遇到的真实场景案例研究。所有可评分的项目都是获得课程证书的必要条件。
Part: 1
Title:Machine Learning
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Part: 2
Title:Supervised Learning
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Part: 3
Title:Unsupervised Learning
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Part: 4
Title:Deep Learning
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Part: 5
Title:The Translator
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Part: 6
Title:Final Project
Description:This is a hands-on opportunity to apply what you have learned in this course and get prepared for the role of a "translator" between the investment team and the data science team. The project is designed to guide you through a case study of a real-life scenario you may encounter in your role as an investment professional who is working with machine learning methodologies. All gradable items in this project are required for you to get a course certificate.
This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills” necessary for investment professionals to stay relevant. In this course, you will learn how to: - Distinguish between supervised and unsupervised machine learning and deep learning - Describe how machine learning algorithm performance is evaluated - Describe supervised and unsupervised machine learning algorithms and determine the problems they are best suited for - Describe neural networks, deep learning nets, and reinforcement learning - Choose an appropriate machine learning algorithm - Describe the value of integrating machine learning and data projects in the investment process - Work with data scientists and investment teams to harness information and insights from within large and alternative data sets - Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.
