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Вернуться к Python and Machine-Learning for Asset Management with Alternative Data Sets

Отзывы учащихся о курсе Python and Machine-Learning for Asset Management with Alternative Data Sets от партнера Школа бизнеса EDHEC

4.4
звезд
Оценки: 199
Рецензии: 51

О курсе

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....

Лучшие рецензии

AT
5 мар. 2020 г.

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.

BB
30 мар. 2021 г.

Was pretty informative, especially getting to see and understand the techniques that large hedge funds might use to determine their investment strategies.

Фильтр по:

26–50 из 52 отзывов о курсе Python and Machine-Learning for Asset Management with Alternative Data Sets

автор: Lê Đ

23 июня 2021 г.

I enjoyed the course. Useful introductions, codes and real-world applications of the codes.

автор: Boya S R

31 июля 2020 г.

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

автор: Luca D

22 мая 2020 г.

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

автор: Sebastián H

29 июля 2020 г.

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

автор: Konstantinos R

1 дек. 2019 г.

Different from the other 3 courses but extremely interesting

автор: Francisco V A

13 июля 2021 г.

Very comprehensive, hands-on course. Strongly recommended

автор: Swarn

29 апр. 2020 г.

Thank you for putting together this amazing class.

автор: Robert N

21 дек. 2019 г.

Interesting and very useful!

автор: TAN L Y

16 июня 2021 г.

Excellent work!

автор: Abel G

8 июля 2021 г.

Great

автор: Chan C

23 нояб. 2020 г.

Picked up interesting insights how alternative data sets can be used for asset management. Covered a lot of different data sets and how they can use used to create features for machine learning models to consume. Significant self study and readings for students to understand and appreciate the lab sessions.

автор: Daniel A C C

15 сент. 2020 г.

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.

автор: M. W

21 апр. 2020 г.

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!

автор: Georges A

4 апр. 2021 г.

It is a course that is relevant in the series, despite the inherent difficulty to quantify this alternate information into valuable data. In the end, it feels somewhat more like art than science. Still interesting.

автор: Luc T

18 февр. 2021 г.

Great overview on Alternative Data types and usage techniques, with useful libraries description in Python. Lack of some explanation / more details on the integration of alternative data sets in financial models.

автор: Hector B

29 янв. 2021 г.

Very good theory and practice. Only comment is the lack of a connection of the quizzes to the notebooks, more questions related to the notebooks would be very beneficial.

автор: Rubens P

15 мая 2020 г.

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

автор: Kostas T

5 мая 2021 г.

Really good! Using real-world dataset and professional experts in the finance industry , unfortunately no live coding but good explanation of the code

автор: Rakesh P

31 июля 2020 г.

The content is really great, but it would have been even better if the code and applications were explained in somewhat more detail.

автор: Palito J E

4 сент. 2021 г.

Great course, combine state-of-the-art Python and machine learning, with the theory and practical test of investment management.

автор: Jean-Luc B

12 апр. 2020 г.

Good course and interesting topics but I guess the quizzes should test the capacity of the students to use the notebooks.

автор: Eran I

24 авг. 2020 г.

Great course, lots of lab session. I was missing some hands on exercises experiencing the data

автор: Andrea M

11 мая 2020 г.

The course is fantastic. The only thing I would add is a session of practical tests.

автор: Steve B

27 дек. 2020 г.

Interesting course and good worked examples in the included Labs.

автор: Elizabeth C W

30 сент. 2020 г.

enjoyed the lab sessions!