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Learner Reviews & Feedback for Python and Machine-Learning for Asset Management with Alternative Data Sets by EDHEC Business School

4.4
stars
134 ratings
33 reviews

About the Course

Over-utilization of market and accounting data over the last few decades has led to portfolio crowding, mediocre performance and systemic risks, incentivizing financial institutions which are looking for an edge to quickly adopt alternative data as a substitute to traditional data. This course introduces the core concepts around alternative data, the most recent research in this area, as well as practical portfolio examples and actual applications. The approach of this course is somewhat unique because while the theory covered is still a main component, practical lab sessions and examples of working with alternative datasets are also key. This course is fo you if you are aiming at carreers prospects as a data scientist in financial markets, are looking to enhance your analytics skillsets to the financial markets, or if you are interested in cutting-edge technology and research as they apply to big data. The required background is: Python programming, Investment theory , and Statistics. This course will enable you to learn new data and research techniques applied to the financial markets while strengthening data science and python skills....

Top reviews

AT

Mar 06, 2020

really interesting applications and good examples. More breadth than depth but a great guide as to what the state of the art is in applying machine learning to more alternative forms of data.

YK

Oct 03, 2020

Detailed Python notebooks clearly explained give valuable tools for analyzing data, and the lectures give ideas what to do with the analyzed data.

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1 - 25 of 33 Reviews for Python and Machine-Learning for Asset Management with Alternative Data Sets

By Loc N

Jan 04, 2020

Way better than the third course in the Specialization. If I have to rank the courses in terms of the organization from high to low, the ranking would be: the first course, this course, the second course, and the final course.

By Fabien N

Feb 06, 2020

Amazing course ! I had been a bit disappointed by Course 3 of the Specialization, but this Course 4 clearly paid back ! The 3-sections structure for each week is really great, the theory is well explained and the lab sessions are very clear, this allows us to really grasp the concepts and be able to use them in the future. In addition, the research application sections greatly open the applications to advanced studies and increase curiosity for the topic. Congrats ! It's one of the best MOOC I had to follow!

By Andrea C

Jan 16, 2020

theory and lab not really synced. Lab not adding lots of value.

By Runar A Ø

Mar 06, 2020

Excellent view into modern financial research in the use of alternative data sets including valuable demonstration in implementation.

By Kevin W

Apr 02, 2020

Great material and knowledgeable lecturers.

However, the Lab sessions aren't relevant to completing most quizzes. So to get more out of the course the student must play with the code outside the context of the class. The disconnect between the two seems like a missed opportunity to force students to look objectively at the Labs and its application.

By Rehan I

Apr 13, 2020

The course is quite good, but the labs were quite rushed - students would benefit from going through the notebooks in more detail with the teachers. Secondly, the 'Application' sections had no accompanying notebooks/labs - students would benefit from being able to replicate some of the findings in the research, at least those of the research by Gideon.

By Marco K

Jul 12, 2020

The first two courses have raised the expectations to a very high level. The last two courses don't meet them at all. Difficulty with modules working (basically lack thereof) makes it difficult to really learn something here.

By Jerry H

May 20, 2020

While not immediately useful for me, I found the course very enlightening. While I was aware of alternate data and its application, I did not have an intuitive feel for how it was done. The course gave a nice introduction to that. Appreciated the coding labs (code is well commented, so I have an excellent resource to help improve my coding knowledge ability). Only suggestion is to rely more on matrix multiplication (as in the last lab) which will make it easier to understand the code and understand the approach being used.

Really liked the structure of the course: 1) theory, 2) labs and 3) application and the links to the many excellent papers. This was a great course structure for people who want to apply the the material.

By Antony J

Oct 15, 2020

This was a superb course, hosted by Gideon, an academic / practitioner who has published in the very best peer-reviewed journals (Journal of Financial Economics and Financial Analysts Journal) and Sean, a talented quant who does a fine job of walking through state-of-the-art techniques in Information Retrieval. I loved the Python library that converts geolocation data into maps, for example!

This is a fine conclusion to an amazing specialization. Thanks!

By Dirk W

Feb 05, 2020

Very well-constructed course, right balance between theory, lab sessions and application. Theory to the point. Lab sessions largely detailed, which is really a forte. Really interesting readings in the application section. Quizzes adapted to the theory, lab sessions and application. No technical issues.

By Alex T

Mar 06, 2020

really interesting applications and good examples. More breadth than depth but a great guide as to what the state of the art is in applying machine learning to more alternative forms of data.

By Hernan S L

May 01, 2020

Great Course! Both guys were awesome! I find the subject really interesting, though I think is hard to get that data. I would really recommend it!

Thanks

By Michinori K

Feb 20, 2020

Great course! Highly relevant and including latest research topics.

Both lectures and labs are very efficient in delivering state-of-the-art contents.

By Yaron K

Oct 03, 2020

Detailed Python notebooks clearly explained give valuable tools for analyzing data, and the lectures give ideas what to do with the analyzed data.

By Lucas F

Apr 30, 2020

Very interesting course. Instructors are quite good. The graded quiz could be less theoretical and a bit more practical/applied.

By HP F

Jun 08, 2020

I liked the lab sessions a lot - this as very useful! The presentation of the research papers was a bit shallow.

By BOYA S R

Jul 31, 2020

Learnt many use cases where machine learning is applied in Finance & Investment domain

By Luca D

May 22, 2020

The most interesting course I have attended for data analysis so far

By Sebastián H

Jul 30, 2020

Very Complete, but is an advanced course, not for beginners.

By Konstantinos R

Dec 01, 2019

Different from the other 3 courses but extremely interesting

By Swarn

Apr 30, 2020

Thank you for putting together this amazing class.

By Robert N

Dec 21, 2019

Interesting and very useful!

By Daniel A C C

Sep 15, 2020

It's a good course, a practical course. However Python lessons are not great as they are in module 1 and 2. I recommend it since it's going to give you a good financial and portfolio management background and understand (not as an expert but understanding the basics) how all that theory works in practice.

By Mirkamil G

Apr 21, 2020

Really interesting and differnt view pot of financial world, both theory and Lab parts are well prepared. But, I still recomannd to add more progamming questions in the Quiz, than students would able to learn more by doing more!

By Rubens P

May 15, 2020

Good course with great practical content and insights into alternative data sets. I would have liked to see some more involved textual analysis techniques.