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.

Pros: Learn some python code and review statistical knowledge (SLR, MLR)

Cons: The python code is outdated and may not usable. So time consuming to update the code.

For Example: pd.DataFrame.from_csv(..\...\AAA.csv) which is commonly used in the course

It is not usable as DataFrame.from_csv has been replaced by pd.read_csv(r'...)

Also for loc has significant changes

The statistics element is basic and there is very little practice coding with Python. Instead, it is more of a demonstration how Python can be used to implement some regressions and basic trading strategies. Informative in showing this, however overall a bit disappointing as there was less Python learning and practice as anticipated/advertised.

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

This is overall a good course; it is well explained and very quick. However, it would benefit with assigning more exercises or ensuring that the labs are more interactive. In this topic, practice makes perfect and is very necessary. Also, the quizzes require clicking on links that do not work.

Good course but I think that economic concepts should be explained in more depth so that we can work better on Jupyter (which is a great way to teach / learn). I also think that more written material with illustrative examples could be included, not just lines of code that generate results.

Course content is valuable from Statistics applied in Python code. Unfortunately, it didn't give enough examples or use cases for Financial Analysis. I'd like to see more stocks market predictions, studies and models using the Statistics concepts explained on this course.

It has wide explanation of statistics basics on the other hand the model development with python applied in finance has too few examples. I would also suggest data acquisition with Yahoo Finance or Google to be explained as it is widely used in financial analysis.

Tough for a person not familiar with statistics and completely new to python. Would have been good to provide more basics to python as well. However, i would believe it'll be very beneficial for one who has already strong foundation in statistics to follow.

first and 4th week was fun and relevent. but the 2nd and 3rd weeks were quite difficult to understand and also lack clarity of what we are learning is how that is going to relate in the trading programming.

Could have done with some more opportunities to write pieces of code in different scenarios; many of the notebooks consisted of just running the prewritten code snippets in order and observing the effects.

Overall good course but needs to clean/improve some of the code/quizes to be consistent. Does not explain Statistics or financial models well but shows basic idea of how to find/use them in Python.

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.

This course is good for someone familiar with the concepts of statistics and linear regression. However, for a complete beginner, it's a little difficult to understand everything taught here.

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.

It's kind of hard to understand to understand the lecturer/professor, but the course material is interesting. I was hoping for a little more programming in Python though!

The video tutorial could have been better, however the notebooks and quiz were perfectly prepared and were instrumental in verifying our understanding of concepts.

this course is really good course to understand python programming

but

1.you need basic and intermediate knowledge of statistics

2. basic knowledge of finance

I think the most valuable part of the course is in week 4 but It was rushed by fast

explanations and I was hoping a better pace in these important topics.

The course was a bit fast-paced and explanations could be more lucid and elaborate. Please increase the number of modules and provide more practice sets.

It's not bad, but it's not great either. I guess it works as a good starting point for further research, but the content is pretty general.

Overall a great experience but was not having a finance background so using these stock market terms for the first time was a challenge.

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

A per-requsite of statistics is required. One should review the basics of statistics before taking the course. Pace is too fast.

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