课程信息

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100% 在线
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可灵活调整截止日期
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中级
完成时间大约为15 小时
英语(English)
字幕:英语(English)

您将学到的内容有

  • Learn the principles of supervised and unsupervised machine learning techniques to financial data sets

  • Understand the basis of logistical regression and ML algorithms for classifying variables into one of two outcomes

  • Utilize powerful Python libraries to implement machine learning algorithms in case studies

  • Learn about factor models and regime switching models and their use in investment management

您将获得的技能

Programming skillsManaging your own personal invetsmentsInvestment management knowledgeComputer ScienceExpertise in data science
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为15 小时
英语(English)
字幕:英语(English)

提供方

北方高等商学院 徽标

北方高等商学院

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 2 小时

Introducing the fundamentals of machine learning

完成时间为 2 小时
8 个视频 (总计 59 分钟), 4 个阅读材料, 1 个测验
8 个视频
Introduction to machine-learning7分钟
Financial applications7分钟
Supervised learning7分钟
First algorithms7分钟
Highlights of best practice6分钟
Unsupervised learning7分钟
Challenges ahead10分钟
4 个阅读材料
Requirements2分钟
Material at your disposal2分钟
Machine Learning for Investment Decisions: A Brief Guided Tour10分钟
References for module 1"Introducing the fundamentals of machine learning"10分钟
1 个练习
Module 1Graded Quiz30分钟
2

2

完成时间为 4 小时

Machine learning techniques for robust estimation of factor models

完成时间为 4 小时
8 个视频 (总计 80 分钟), 2 个阅读材料, 1 个测验
8 个视频
Introducing Factor Models7分钟
Typology of factor models9分钟
Using factor models in portfolio construction and analysis10分钟
Penalty methods9分钟
Setting factor loadings and examples7分钟
Shrinkage concepts7分钟
Lab session - Jupiter notebook on Factor Models20分钟
2 个阅读材料
References for module 2"Machine learning techniques for robust estimation of factor models"10分钟
Information on Jupyter notebook - Factor models10分钟
1 个练习
Module 2 Graded Quiz1小时
3

3

完成时间为 2 小时

Machine learning techniques for efficient portfolio diversification

完成时间为 2 小时
7 个视频 (总计 59 分钟), 2 个阅读材料, 1 个测验
7 个视频
Benefits of portfolio diversification8分钟
Portfolio diversification measures12分钟
Principle component analysis8分钟
Role of clustering6分钟
Graphical analysis8分钟
Selecting a portfolio of assets7分钟
2 个阅读材料
References for the module "Machine learning techniques for efficient portfolio diversification"10分钟
Reference for the module "Selecting a portfolio of assets"10分钟
1 个练习
Module 3 Graded Quiz45分钟
4

4

完成时间为 3 小时

Machine learning techniques for regime analysis

完成时间为 3 小时
7 个视频 (总计 65 分钟), 4 个阅读材料, 1 个测验
7 个视频
Portfolio Decisions with Time-Varying Market Conditions10分钟
Trend filtering6分钟
A scenario based portfolio model8分钟
A two regime portfolio example7分钟
A multi regime model for a University Endowment9分钟
Lab session- Jupyter notebook on regime-based investment model15分钟
4 个阅读材料
Information on the "trend filtering" video2分钟
Information on "scenario based portfolio model" video2分钟
References for the module "Machine learning techniques for regime analysis"10分钟
Information on Jupyter notebookon regime-based investment model10分钟
1 个练习
Module 4 Graded Quiz1小时

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关于 Investment Management with Python and Machine Learning 专项课程

The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language through a series of dedicated lab sessions....
Investment Management with Python and Machine Learning

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