关于此 专项课程
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100% 在线课程

立即开始,按照自己的计划学习。

灵活的计划

设置并保持灵活的截止日期。

初级

完成时间大约为1 个月

建议 13 小时/周

英语(English)

字幕:英语(English)

您将学到的内容有

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    Write custom Python code and use existing Python libraries to build and analyse efficient portfolio strategies.

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    Write custom Python code and use existing Python libraries to estimate risk and return parameters, and build better diversified portfolios.

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

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    Gain an understanding of advanced data analytics methodologies, and quantitative modelling applied to alternative data in investment decisions

您将获得的技能

Risk ManagementPortfolio construction and analysisPython programming skillsImplementation of data science techniques in investment decisionsPortfolio Optimization

100% 在线课程

立即开始,按照自己的计划学习。

灵活的计划

设置并保持灵活的截止日期。

初级

完成时间大约为1 个月

建议 13 小时/周

英语(English)

字幕:英语(English)

专项课程的运作方式

加入课程

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实践项目

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获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

此专项课程包含 4 门课程

课程1

Introduction to Portfolio Construction and Analysis with Python

5.0
5 个评分
课程2

Advanced Portfolio Construction and Analysis with Python

课程3

Python and Machine Learning for Asset Management

课程4

Python and Machine-Learning for Asset Management with Alternative Data sets

讲师

Avatar

Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.
CEO
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Lionel Martellini, PhD

EDHEC-Risk Institute, Director
Finance
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John Mulvey - Princeton University

Professor in the Operations Research and Financial Engineering Department and a founding member of the Bendheim Centre for Finance at Princeton University
Finance

关于 EDHEC Business School

Founded in 1906, EDHEC is now one of Europe’s top 15 business schools . Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform. These various components make EDHEC a centre of knowledge, experience and diversity, geared to preparing new generations of managers to excel in a world subject to transformational change. EDHEC in figures: 8,600 students in academic education, 19 degree programmes ranging from bachelor to PhD level, 184 professors and researchers, 11 specialist research centres. ...

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分,系统会自动为您订阅完整的专项课程。访问您的学生面板,跟踪您的进度。

  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

  • Approximately 4 months to complete

  • This digital Specialization program is meant to be self-contained and no prior knowledge or Python or portfolio analysis is assumed or required. On the other hand, learners are expected to show a good dose of enthusiasm for, and interest in, the subject of data science applied to investment management.

  • We encourage you to complete the whole series, starting with “Introduction to portfolio construction and analysis with Python” and “Advanced portfolio construction and analysis with Python”, before taking the “Python Machine-learning for investment management” course. Then,  you will be able to put  final touch on your understanding of how new data science techniques can be used in investment decisions by taking the course “Python machine-learning for investment management with alternative data sets”.

  • Upon completing the Specialization, learners will be able to build their own custom Python code and use existing Python libraries to optimize portfolios and implement sophisticated risk measurement and risk management techniques. They will also be able to use powerful machine learning techniques applied to traditional or alternative data sets to implement improvement investment decisions.

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