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Learner Reviews & Feedback for Python and Machine Learning for Asset Management by EDHEC Business School

3.1
stars
317 ratings

About the Course

This course will enable you mastering machine-learning approaches in the area of investment management. It has been designed by two thought leaders in their field, Lionel Martellini from EDHEC-Risk Institute and John Mulvey from Princeton University. Starting from the basics, they will help you build practical skills to understand data science so you can make the best portfolio decisions. The course will start with an introduction to the fundamentals of machine learning, followed by an in-depth discussion of the application of these techniques to portfolio management decisions, including the design of more robust factor models, the construction of portfolios with improved diversification benefits, and the implementation of more efficient risk management models. We have designed a 3-step learning process: first, we will introduce a meaningful investment problem and see how this problem can be addressed using statistical techniques. Then, we will see how this new insight from Machine learning can complete and improve the relevance of the analysis. You will have the opportunity to capitalize on videos and recommended readings to level up your financial expertise, and to use the quizzes and Jupiter notebooks to ensure grasp of concept. At the end of this course, you will master the various machine learning techniques in investment management....

Top reviews

ST

Apr 9, 2020

The topics covered in this course are really interesting. I learned a great deal by studying various papers covered in this course - Thank you to both instructors!

AR

May 11, 2022

Very nice course sharing many types of knowledges around data / cleaning / type of data / several algorithms / organised Python coding

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51 - 75 of 131 Reviews for Python and Machine Learning for Asset Management

By Moreno C

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Jul 6, 2020

The content of the course is very interesting and properly explained by the instructors.

Unfortunately, the Lab session with Jupiter are too concise.

Given the complexity of the issues treated, they should last for at least an hour.

Instead, they rarely go beyond 15minutes with the result that the topics of the Labs end up being quickly and superficially explained.

By Kazuto A

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Aug 2, 2020

If you compare this course with the previous two courses, you will find disappointment.

Lab session is not well structured step by step, providing you with complex codes without much explanation.

But if you look at the bright side, the course gives you a big picture of machine learning application in the area of investment management.

By Rodrigo F R

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Nov 15, 2020

There are good insights about the applicability of ML techniques in investment management. However, the course structure and material are not at the same level of the other previous 2 courses of this specialization. It is much more harder to follow. Not always theory and lab classes are in sync.

By Kostas T

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Apr 24, 2021

Some live coding and further explanation of some functions should be added, like in the first two MOOCs. This would give the chance of better understanding while practicing on the implementation of ML algos. That way quiz could be enhanced with more implementation of the code questions.

By Eran I

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Aug 5, 2020

The course is too high level, and provide some introduction to ML. The course materials (i.e. lab sessions, in session quiz questions and rated quizzes) are not accurately drafted. Missing some additional insights on the parameters used for each ML method and its impact

By Alexander D

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Mar 1, 2020

Overall, this course was a lot weaker compared to the previous two of this specialization. While the lecture videos were decent, the lab sessions were just bad. Screenshots of code on slides and unenthusiastic presenters.

By Adam C

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Dec 23, 2020

The class was okay but not enough detail was provided on the coding process in the labs. They were difficult to follow and had little to do with the material that was tested.

By Scott M

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Sep 30, 2023

A lot of material but very little explanation on Machine Learning concepts. If the professor and lab instructors took the time to go in depth this could be a good course.

By Karl J

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Oct 28, 2020

A great basic overview of machine learning methods applied to finance, but the details are sparse. Assessments could be better aligned to objectives.

By sven h

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Aug 15, 2020

this module is too theoretical - the other modules in this specialization are more hands on and combine theory and practice better.

By Khursheda F

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Apr 3, 2020

did not have an opportunity to play with the code, did not have the chance to build my own models to practise the learned material

By Norbert J

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Aug 17, 2020

I think that the practical lab content was not very well connected to the theoretical part in this course of the specialization.

By Francisco V A

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Nov 17, 2020

This is the course that I've liked the least. The labs seem to be almost recommended and not an integral part of the material.

By Alex H

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Aug 19, 2020

Poor exercises and relatively simple and obvious theory, however, some coding parts and theoretical insights very useful

By Giuseppe

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Jan 9, 2021

the course is not well structured, however the content is interesting and the course covers different topics

By David M

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Dec 31, 2020

It would be better if the lectures and the materials correspond with the quizzes and assignments.

By Edwin D R D

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Jun 7, 2020

It is somewhat disorganized and repeats many topics from previous courses of the specialization.

By Bhavya J

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Jun 26, 2020

The Code was not well explained in the lectures however the concepts put forward are valuable

By Brian H

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Feb 19, 2020

I liked the content, but missed the practical application like in the previous courses.

By Pedro B

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Aug 24, 2020

Lab sessions could explore in more details the coding used for problem solutions.

By Liang Y

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Dec 19, 2022

Informative but a little bit confusing with code parts and some techniques.

By Clément p

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Nov 6, 2021

Manque d'exercice pratique mais approche très intéressante, trop guidée

By Aayush T

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Jun 11, 2020

The lab sessions could be way better. The quality of tests is bad

By Rui Z

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Jul 31, 2020

The lab session is not well instructed.

By Chow K M

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Jul 21, 2021

Feedback on quiz can be improved.