Informações sobre o curso
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100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 14 horas para completar

Sugerido: 5 weeks - 2/3 hours per week...

Inglês

Legendas: Inglês
User
Os alunos que estão fazendo este Course são
  • Financial Analysts
  • Data Scientists
  • Analysts (General)
  • Data Engineers
  • Engineers

O que você vai aprender

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

  • Check

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

  • Check

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

  • Check

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

Habilidades que você terá

Programming skillsManaging your own personal invetsmentsInvestment management knowledgeComputer ScienceExpertise in data science
User
Os alunos que estão fazendo este Course são
  • Financial Analysts
  • Data Scientists
  • Analysts (General)
  • Data Engineers
  • Engineers

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 14 horas para completar

Sugerido: 5 weeks - 2/3 hours per week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
2 horas para concluir

Introducing the fundamentals of machine learning

8 vídeos (Total 59 mín.), 4 leituras, 1 teste
8 videos
Introduction to machine-learning7min
Financial applications7min
Supervised learning7min
First algorithms7min
Highlights of best practice6min
Unsupervised learning7min
Challenges ahead10min
4 leituras
Requirements2min
Material at your disposal2min
Machine Learning for Investment Decisions: A Brief Guided Tour10min
References for module 1"Introducing the fundamentals of machine learning"10min
1 exercício prático
Module 1Graded Quiz30min
Semana
2
4 horas para concluir

Machine learning techniques for robust estimation of factor models

8 vídeos (Total 80 mín.), 2 leituras, 1 teste
8 videos
Introducing Factor Models7min
Typology of factor models9min
Using factor models in portfolio construction and analysis10min
Penalty methods9min
Setting factor loadings and examples7min
Shrinkage concepts7min
Lab session - Jupiter notebook on Factor Models20min
2 leituras
References for module 2"Machine learning techniques for robust estimation of factor models"10min
Information on Jupyter notebook - Factor models10min
1 exercício prático
Module 2 Graded Quiz1h
Semana
3
2 horas para concluir

Machine learning techniques for efficient portfolio diversification

7 vídeos (Total 59 mín.), 1 leitura, 1 teste
7 videos
Benefits of portfolio diversification8min
Portfolio diversification measures12min
Principle component analysis8min
Role of clustering6min
Graphical analysis8min
Selecting a portfolio of assets7min
1 leituras
References for the module "Machine learning techniques for efficient portfolio diversification"10min
1 exercício prático
Module 3 Graded Quiz45min
Semana
4
3 horas para concluir

Machine learning techniques for regime analysis

7 vídeos (Total 65 mín.), 4 leituras, 1 teste
7 videos
Portfolio Decisions with Time-Varying Market Conditions10min
Trend filtering6min
A scenario based portfolio model8min
A two regime portfolio example7min
A multi regime model for a University Endowment9min
Lab session- Jupyter notebook on regime-based investment model15min
4 leituras
Information on the "trend filtering" video2min
Information on "scenario based portfolio model" video2min
References for the module "Machine learning techniques for regime analysis"10min
Information on Jupyter notebookon regime-based investment model10min
1 exercício prático
Module 4 Graded Quiz1h

Instrutores

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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
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Lionel Martellini, PhD

EDHEC-Risk Institute, Director
Finance

Sobre 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. ...

Sobre Programa de cursos integrados Investment Management with Python and Machine Learning

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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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