Chevron Left
Retour à Python and Statistics for Financial Analysis

Avis et commentaires pour d'étudiants pour Python and Statistics for Financial Analysis par Université des sciences et technologies de Hong Kong

4.4
étoiles
2,265 évaluations
503 avis

À propos du cours

Course Overview: https://youtu.be/JgFV5qzAYno 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....

Meilleurs avis

EJ
3 août 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.!

LH
23 mars 2020

A very good introduction course to python programming and it has a perfect combination with statistics, which makes financial analysis more interesting and refresh my mind on it, thanks.

Filtrer par :

426 - 450 sur 500 Avis pour Python and Statistics for Financial Analysis

par Reo W

31 mai 2020

Overall good, the professor is delicated and responds to the forum actively. But the course could be better designed. Even though I have learned the knowledge of statistics, econometric, and python and got a 100% certificate, the course is still difficult for me to digest. I have to pause the video and think 5-8 times per video. The pace is so fast that some usages of the python or applicaions of finance equations lack sufficient illustration.

par Andrew C

16 oct. 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.

par Kwok T F E

25 juil. 2020

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

par Dawid V

17 avr. 2020

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.

par Đan T L

4 juil. 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

par Alexander D

3 déc. 2020

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.

par Miranda G

10 sept. 2020

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.

par Cesar D

5 mai 2020

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.

par Eduardo F R

2 sept. 2020

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.

par Mingyue W

14 juin 2020

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.

par Sushil K

25 avr. 2020

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.

par William B

16 juil. 2020

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.

par Ricardo P

16 mai 2020

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.

par YI L

13 oct. 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.

par Abhay N

15 déc. 2019

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.

par Anand S

7 sept. 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.

par Michael O

25 oct. 2020

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!

par Ketan V

11 janv. 2020

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

par Sagnik S

10 août 2020

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

par Andres M M

22 juin 2020

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.

par Shashank G

11 mai 2020

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.

par Lisa W

16 mars 2020

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.

par Mridul w

29 déc. 2019

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

par King Y C

8 févr. 2019

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