Most of the links didn't work.

It was a bit hard to follow

need to improvment

average

...

k

The knowledge side, it is very good and relevant to finance.

But the tech and coding side which is the main thing i'm looking forward, is very bad. The instruction is not step by step and not clear in application. I don't even know where the files are and so i cannot import in the jupyter notebook.

The courese, first, need to tell learners the over view of python that learners need python installed as a programming language and a separate IDE like a notebook to code on, such as visual studio code, or jupyter notebook, because coding is not like using MS offfice, just install and go.

Third, the syntax taught is very bad and outdated. At the import phase, I cannot even use the syntax of "Data frame.from csv" in python 3.10. Assume that it can be run in the environment of cousera, how can I use python in the working environment if you taught me such outdated syntax.

Some links were broken, or had other issues. The course is primarily a flash introduction to regression analysis. I was hoping to learn more python skills. Might be worthwhile if you are already comfortable with multiple regression and python but are specifically interested in financial time series. As it primarily assumes stock prices changes will be normal I expect all the material is utterly useless in the real world (real stock world shifts in stock price tend to follow Pareto distribution).

I really cannot recommend this course. Course tries to touch two major topics: Financial Risk Management and Statistics. In both disciplines course is only scratching surface of the subject without going into any details. Just for quantitive estimation, FRM is 100+ hours of material, Statistics - another 200+ hours. Whole course contains definitely less than 4 hours of lectures.

On the other hand - course is some sort of source of topics you need to find yourself over Internet and learn yourself.

In evaluating this course, it took me a while to identify the target audience from the course materials. The statistical content is too fast-paced and lacking detail for newcomers, and that the Python content is de-emphasised. I suppose that this course is a good introduction for those outside finance seeking an introduction. Looking at this course as exercises to improve my Pandas knowledge, I left disappointed because there was no course Python assignment in implementing a trading strategy.

The proficiency level of English of the instructor is very poor. I don't know about English mother tongue speakers but I reckon that for everyone else the instructor was almost impossible to follow. I had to make hundreds of pauses because I couldn't understand what the instructor was saying and the subtitles are horrible as well. It easily took me x3 the time to complete because of the poor English speaking skills of the instructor.

I have a PhD in econometrics - took this course to see if it would be useful to some of my team - gleans over complex issues way to fast but given the length that is understandable - my issues with this course are (a) the Jupiter notebooks are complete already so don't make students think and (b) there should be a great deal of included warnings with references for students to dig deeper outside of the class

Part of the code doesn't work. To fix it it is needed to go to Python documentation and do research

A lot of statistics concept are not quite well explained. The course should include more detailed explanations or at lease some links where the this information can be studied

The results of the trading system implemented in the curse are not the one that you will obtain

i have to give two stars because I can't be able to do the lab session, I'm always told you have run out of time so I didn't do any lab session, finishing the course without any lab session is very worried which I have ended up knowing nothing despite completion, please make it flexible for me to do the lab session to know more

Too many mistakes in the use of English throughout the course made it hard for me to follow the course properly without getting annoyed. The instructor's English was terrible as well, just too many mistakes, which made it impossible to follow without subtitles. The content was good though which is why it deserves two points.

I was hoping for a little more from this course. While it effectively combines statistics, finance and python, it does not go into great detail in any of the three. There are spelling mistakes and the audio quality is not great. For me the most useful part was learning the python functions and syntax.

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.

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.

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.

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 :)

- Instructor's English is hard to understand

- Materials are not high quality. There are many typos, links in exams do not work, "none of the above" appears as first option, some Pyhton methods are not up-to-date

felt very hard to follow, didn't get most of the lectures, and much of the interactive activities I could don't really follow through. Generally, this is a course that I could get on youtube for better and free.

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".

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

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