About this Course

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 13 hours to complete

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

English

Subtitles: English
User
Learners taking this Course are
  • Data Scientists

What you will learn

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

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

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

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

Skills you will gain

Programming skillsManaging your own personal invetsmentsInvestment management knowledgeComputer ScienceExpertise in data science
User
Learners taking this Course are
  • Data Scientists

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 13 hours to complete

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

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Introducing the fundamentals of machine learning

8 videos (Total 59 min), 3 readings, 1 quiz
8 videos
Introduction to machine-learning7m
Financial applications7m
Supervised learning7m
First algorithms7m
Highlights of best practice6m
Unsupervised learning7m
Challenges ahead10m
3 readings
Requirements2m
Material at your disposal2m
References for module 1"Introducing the fundamentals of machine learning"10m
1 practice exercise
Module 1Graded Quizz30m
Week
2
4 hours to complete

Machine learning techniques for robust estimation of factor models

8 videos (Total 80 min), 2 readings, 1 quiz
8 videos
Introducing Factor Models7m
Typology of factor models9m
Using factor models in portfolio construction and analysis10m
Penalty methods9m
Setting factor loadings and examples7m
Shrinkage concepts7m
Lab session - Jupiter notebook on Factor Models20m
2 readings
References for module 2"Machine learning techniques for robust estimation of factor models"10m
Information on Jupyter notebook - Factor models10m
1 practice exercise
Module 2 Graded Quizz1h
Week
3
2 hours to complete

Machine learning techniques for efficient portfolio diversification

7 videos (Total 59 min), 1 reading, 1 quiz
7 videos
Benefits of portfolio diversification8m
Portfolio diversification measures12m
Principle component analysis8m
Role of clustering6m
Graphical analysis8m
Selecting a portfolio of assets7m
1 reading
References for the module "Machine learning techniques for efficient portfolio diversification"10m
1 practice exercise
Module 3 Graded Quizz45m
Week
4
3 hours to complete

Machine learning techniques for regime analysis

7 videos (Total 65 min), 2 readings, 1 quiz
7 videos
Portfolio Decisions with Time-Varying Market Conditions10m
Trend filtering6m
A scenario based portfolio model8m
A two regime portfolio example7m
A multi regime model for a University Endowment9m
Lab session- Jupyter notebook on regime-based investment model15m
2 readings
References for the module "Machine learning techniques for regime analysis"10m
Information on Jupyter notebookon regime-based investment model10m
1 practice exercise
Module 4 Graded Quizz1h

Instructors

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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

About 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. ...

About the Investment Management with Python and Machine Learning Specialization

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

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.