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Voltar para Python and Statistics for Financial Analysis

Comentários e feedback de alunos de Python and Statistics for Financial Analysis da instituição Universidade de Ciência e Tecnologia de Hong Kong

433 classificações
88 avaliações

Sobre o curso

Course Overview: Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data. By the end of the course, you can achieve the following using python: - Import, pre-process, save and visualize financial data into pandas Dataframe - Manipulate the existing financial data by generating new variables using multiple columns - Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts - Build a trading model using multiple linear regression model - Evaluate the performance of the trading model using different investment indicators Jupyter Notebook environment is configured in the course platform for practicing python coding without installing any client applications....

Melhores avaliações


Jul 05, 2019

The videos in this course are exceptional and very interesting. The Jupyter notebooks provide a good template for applying the methods and techniques.


Jan 21, 2019

Perfect for the beginning to intermediate python programmer who wants to utilize finance data to make decisions (i.e. trading).

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76 — 88 de {totalReviews} Avaliações para o Python and Statistics for Financial Analysis

por King Y C

Feb 08, 2019

The course is somehow overlapped with the course ISOM2500.Moreover,i do not think that I have really learned a lot regarding Python.

por Sui W T

Feb 10, 2019

It's a bit difficult for students who have no either coding or statistic background to understand the content of the course.

por Mehul V

Mar 11, 2019

Many things were left unexplained. A step by step procedure wasn't followed.

por Krzysztof P

Jun 29, 2019

I have mixed feelings about the course. It shows very practical aspects of building trading stategy in Python, which is still quite unique topic here. It also offers a lot of practice and ready to use and modify solutions delivered as Jupyter notebooks. This course definitely expect you to know a bit about statistics and also to know Python programming, on basic level at least. On the other hand I think the course does not cover the topic deep enough, we've got only some simple linear regression model based on some not-so-creative feature engineering. It does not cover such aspects as HFT vs swing trading strategies, using slipage and transaction costs to evaluate strategy, managing invested capital and many more. I've expected a bit more, to be honest. The course is well done as ready-to-use implementation of very simple concept - but there's nothing more to expect here.

por Đan T L

Jul 04, 2019

Interesting and easy to understand for people with basic background or have basic knowledge about finance or statistic. However, I wish some of the videos may have explained more about how to use the data to solve real life issues. Even though some of the practices may explore it, it appears not deep enough for me

por Luke L

Sep 08, 2019

Lots of info to learn. Does not challenge you to actually write the code, which is a big drawback.

por Anand S

Sep 07, 2019

This is a course more for statistics than python. All we understand is how to use the Python libraries and their functions to compute statistical data.

90% Statistics

10% Python.

por YI L

Oct 13, 2019

Videos are not really connected to the practice. Some finance and statistic stuff is simply mentioned and directly used without enough explanation. I finished the course with help from Google.

por Andrew C

Oct 16, 2019

I wish the concepts in this course were gone into more in depth. They aren't necessarily difficult but they can get complex and when the instructor spends an accumulation of 30 or less per module it is hard to fully understand. More practice is needed as well. All the code was done for you except for just a few lines. People who learn by application will not gain much from this course.


Aug 13, 2019

Lectures are not very informative. Things are said directly and not explained well. Sadly I paid $50 for this.

por Nicolas P

Sep 01, 2019

I would change the title. It has little practical content on trade, and explains more statistical methods.I would call it "how to use and graph statistics in python, with some trade samples".