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Learner Reviews & Feedback for Python and Statistics for Financial Analysis by The Hong Kong University of Science and Technology

3,248 ratings

About the Course

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....

Top reviews


Apr 13, 2021

Un curso con una perceptiva muy refrescante en cuanto a los conceptos técnico-estadísticos y sumamente prácticos. e incluso baratos, de implementar dentro del mundo de la inversión. Muy buen trabajo.


Aug 3, 2019

Great course! Very didatic explanations about financial and statistical concepts also with some interesting practical Python for Finance! Looking forward for new courses from same Univ. and prof.!

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701 - 725 of 735 Reviews for Python and Statistics for Financial Analysis

By Andrey P

Apr 29, 2022

Don't waste your time. The statistics part isn't explained well enough. Python code, which this course provides, is slow and uses outdated concepts. The idea of predicting stock prices using linear models is just a gem! If you are new to python, the course can show you how not to write code.

By Jonathan Z

Sep 29, 2021

Course is good but (a) some Python bits are not up-to-date and (b) final week exam questions should be updated and brought in sync with either lectures or the lectures need to be updated. If Google has a different answer than the course, well, that's not a great place to be in.

By Rohit P

Feb 7, 2022

Course uses <pd.DataFrame.from_csv >. This has been discarded by Python. Since I am begineer to Python and on assumtion that such discarded notations will again be used going further in course, I have no choice but leave the course in first week itself.

By Laleh N

May 28, 2020

i am happy with subject and course syllabus but if the data that the lecturer worked on them, was available the course would be much more useful,

without the data, it was just some code that we were watching.

thank you coursera :)

By Nicolas P

Sep 1, 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".

By Vikram N

Feb 25, 2022

Does not explain technical terms well. I had to search online to understand much of this content. Some of the quiz questions related lab to are not explained in course / lab

By Mohini J

Mar 21, 2020

The course tried to cover a lot but wasn't really helpful for those who didn't have basic knowledge of either Python or Statistics

By Panguluri B T

Jul 10, 2020

Poor Explanation of topics, was in a very hurry to complete than in explaining the concepts in depth. Did not reach expectations.

By Jacob G

Jun 23, 2021

More coding please. I was looking for more linear modeling examples and implementation. The rest was relatively easy.

By Andrew D

May 24, 2022

Not enough detail. Lectures have good material but a lot of information is presented too quickly. Labs are good


Aug 13, 2019

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

By Victor H C C

Jun 17, 2022

weak, not really good course, just showing some basics of data analisys and concepts.

By Danny w

May 6, 2020

The teacher need to learn better pronunciation and slower pacing

By wegdan

Feb 24, 2021

video lecturing lacks clarity and big picture context

By Eliad H

Mar 12, 2019

very basic,

not improving python skills

By Wickson H

Feb 28, 2022

Too difficult to beginner

By Lubie W

Aug 9, 2020

This course teaches statistics more than Python coding. The codes are not well explained or even not explained by the instructor. The instructor spent more time on statistics concepts than going through the Python coding. I learned very little about Python in this course.

By Liem J L

Nov 15, 2019

Should be better explained. Could not get past the first few lines in the practical. Looked at the discussion board and people were saying it was because the course is outdated and the code he explained might not even work with the version we were using

By Anas A H H

Jun 16, 2021

1- t​he language spoken is not clear (I had t oread the subtitles more than listening which was a horrible experience)

2​- the labs are bot built in the right way, lots of errors and lots of data changes that effected the application of the commands

By Jack M

Apr 26, 2020

Horribly worded questions. Difficult to understand the lecturer. Week 1 was good to practice python. Week 2 was awful.

By Sean S

Nov 26, 2019

The code examples and quizzes have not been properly reviewed and there were multiple mistakes in them.

By Marshall T

May 26, 2020

codes are not updated to python 3. Also little opportunity to apply codes in IDLE/Anacdona yourself.

By Christeen P

Mar 12, 2021

Disorganized, and the quizzes are not testing abilities nor knowledge but just quantitative skills.

By Avnish A

Mar 26, 2020

very vague and non detailed explanations from week 2. almost impossible to catch up.

week 1 was good

By Pedro J G R

Oct 14, 2021

Very complex explanations (even if you learnt statistic before) and then zero practice. A fake!