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

3,160 évaluations
701 avis

À propos du cours

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....

Meilleurs avis


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.


25 mars 2020

Very clear explaining of the significant aspects when structuring a financial analysis, applicable in many forms of data if you don't want to make predictions only for the stock market.

Filtrer par :

26 - 50 sur 718 Avis pour Python and Statistics for Financial Analysis

par Jessica P

3 août 2021

zero walkthroughs. have NO idea what to do. course is incomprehensible

par Antonio C

26 févr. 2022

The course is well done. I appreciate that some minor things about Phyton are ommitted in order to explain the important things more rapidly. If you have never coded before (like me) and you want to follow this course seriosuly, understanding every line of code, then you have to do additional research online, to read for example the exact synthax of a certain method or function that is being used.

I truly wish there was a follow up to this course, to go more in depth and to see more examples. Sometimes the accent of the teacher and the wrong (english) subtitles can make it harder to understand certain part, one funny example is "shot" a stock instead of shorting it. Only in very few instances it actually made it tougher to understand certain parts as for example the verb-noun agreement was not easy to understand, english is not my first language so take what I said with a grain of salt as well! Thanks a lot for this course! Again, I really hope you decide to do a Part 2 ! I would enroll immediately

par Harald M

20 janv. 2021

This course is challenging if you have not yet gained a sufficient understanding of both statistics (i.e., normal distribution, linear regression, etc.) and Python (e.g., list comprehension, how to call class methods, etc.). Other than that it is a great course to show how you can blend both and build a trading model that can be applied to the market. The course will guide you step by step from explaining the different libraries used (pandas, statsmodels, numbpy, matplotlib) to both analyze and visualize the data, how to build your trading model, how to diagnose and test your model, and finally how to evaluate its profitability. A great course for everyone who would like to see in more detail how you actually build a trading model with Python and statistics. Very recommendable if you are willing to put in the work.

par Mike H

13 mai 2020

The Coursera overview of this course is exactly what it turns out to be. Prof. Wan does a nice job of balancing this 3-legged stool: 1) a bit of Python (mostly about the pandas and numpy libraries), 2) basic Financial modeling for informed trading, and 3) the long leg of the stool - statistics!

If you haven't had like stats 101 and 102 you will be running hard to digest this intensely powerful information. For me this was first a review but then took me into places I hadn't been yet. I'm still going over it. The statistical principles shown here can be applied to many different real world situations. It could be categorized as 'supervised learning'.

The Python coding (library implementations of the math formula/equations) is made seamless with the Jupyter notebook examples. Drink the Kool Aid!


9 sept. 2020

I audited the course for free and I liked it very much. I feel I learned a lot. I wanted to purchase the shareable cerfitificate, after I completed all my work and passed all the tests (I didn't purchase it when a message offering the cerfificate kept popping up during the course). However, the instructions to purchase the cerficate after having taken the course leave a lot to be desired. It should be easier. There should be a button, right on the course's page that I could just click on in order to pay and then be done. The instructions sent me all over the place, from page to page. I'm still not able to find a way to purchase my cerficate . Frustrating! I guess I can do without it. Other than that, Great Course!

par John Y

28 avr. 2022

I am an software engineer with little statistic knowledge before. This course is a little bit challenging for me because I need to read a lot of extra statistics knowledge from Google otherwise it is difficult to understand the concepts, especially for week 3 and 4. I have repeatly watched each video for 3 to 4 times and finally found that Prof Xu has done his best to explain some basic concept on Normal distribution, CLT etc. You just need to spend time to digest these concept which has applied to his sample code. Overall this is a very useful course. I will try to use the knowledge to code some new investment strategy for myself.


9 mai 2020

I, Anjali Krishna R, after completing this course can say that this course really helped me to have a clear understanding of my knowledge in the field of statistics and cleared some doubts which I had earlier. It also helped to know some more concepts of using python. Earlier I thought python is so difficult etc. Totally, I am really thankful and sincerely thanking the professor for everything ie in the field of your explaining those facts and the subtitle. Really I enjoyed doing this course and may it help me to achieve a career with this course. Thank You.

par Tim B

1 déc. 2019

Excellent introduction course to use Python and Statistics for stock market data analysis and trading strategies. I really enjoyed the course and it is well organized and set up, it kept me motivated to complete the course. I did not have any prior Python experience but managed to follow the course and you do not need to have Python installed on your computer. I agree that you will definitely get more out of this course if you have prior knowledge of basic statistical concepts. Overall, a fantastic course.

par Matthias H

27 août 2020

This course is exceptional. If you look to apply statistical analysis to financial market data by the use of python, I don't believe that you find something better than this. It is helpful, if you are familiar with basic statistical concepts (descriptive and inferential statistics as well as linear regression), and if you are familiar with python and its data sciences packages. Otherwise you may use the course to deepen your knowledge in these areas on the go. I truly can recommend this course.

par Christopher S C

1 janv. 2021

Good course for people who want a quick introductory into using Python and Statistics for Finance. It covers quite a lot but does not provide too much detail which needs to be researched outside of the course. Given I had a little bit of experience in Python and worked in Finance and Statistics for several years this course was a good balance for me however if you have no experience it might be struggle to make the jumps with each week without more context/ detail which the course lacks.

par Shuhong L

7 févr. 2019

this is a wonderful course with well-prepared videos to illustrate and well-organised Notebook for practice. the final score you will get is only depended on four quizzes, but it is always useful for you to watch videos carefully and try very best to type codes on Notebook provided for you, which can also benefit your quizzes. you can some basic sentence structure of Python and grasp the practical tool to build a model to make financial inference. with light workload, you can get a lot.

par Sumedh K

11 août 2019

One of the finest course in this field. I have already done 2 courses on Python and Statistics for Finance and this was the third one. Amongst the three this is easily the easiest to understand and best course for sure. I will look forward to course from this professor or university in the future. Week 3 and Week 4 from the course are like a gold mine for any learner. And the jupyter notebook exercises give just the required practice immediately after the concept is learned.

par Tobias T

22 janv. 2019

It is a very good course to learn the basics in python to analyze financial stock market data. However, if you don't have prior knowledge to statistics and financial data (variance, histograms, regressions, value at risk, hypothesis testing, ...), the course might be to fast to understand the background, because you cannot explain all these things properly in 2-3 hours of video. But I guess most people who want to analyze stock data in python have this knowledge.

par Harshvardhan S T

1 mai 2020

I'm happy to have done this course because I just wanted to brush up on my python skills. All the finance and statistics bit of this course was already covered by my undergraduate degree ( in Elements of econometrics), which helped me get done with this course within 12 hours but I would still suggest other students take your time in finishing it. Thank you, Mr. Xuhu Wan, you were of great help, and thank you Coursera for providing me with this informative course.

par Facundo M L

18 mai 2020

I am a student in his Statistics class at the Hong Kong University of Science and Technology, and this course helped me review key statistical concepts that we saw in class. Moreover, this course serves as a great introduction to Python. I am now able to make my own prediction models, which will come in handy as I will be able to make more accurate decisions. I am looking forward to use statistics to better understand the world around me. Thank you Professor Wan!

par Pushkar G

9 févr. 2022

T​his is a good course for beginners. It introduces the basic concepts in a nice manner and you can understand things easily. If you have a prior idea of python, statistics and finance it will make your journey smooth. The videos are helpful and easy to follow. While the jupyter notebooks are great and make it convenient for anyone to attend, i would suggest that you try and do this on your own standalone work desk as well to gain a better perspective.

par Bernardo A

30 nov. 2020

Excelente curso para una introducción en Python. Muy útil para aquellos que no tienen conocimientos previos de esta herramienta, además brinda la oportunidad de emplear las bondades de la herramientas en el análisis financiero, en especial en trading. El tutor y los recursos utilizados se conjugan muy bien para ofrecer una agradable experiencia de aprendizaje en temas de estadística, machine learning y análisis financiero. Muy recomendable este curso.

par 20-064 D A

27 juin 2022

This article provides a broad application of Python, finance and statistics. Actually, I'm looking for classes like these. I haven't found any yet. Atlast takes this as consolation. This was what I needed. This course cannot be designed as simply as other courses. This really needs to be done once. Thank you to both the person who devised the course and the instructor, Mr.Xuhu Wan, for their careful attention to detail in delivering the information.

par João A A

1 déc. 2020

It is an interesting course that will introduce you to the very basics of financial analysis. For those not familiar to Python, it is also a nice introduction to use Python and a few important libraries, such as "pandas". Note that the course does not give very detailed information about Financial Theory. I recommend this course if you want to have a quick introduction to Python analysis applied to Financial Market. It is a very enjoyable course.

par Roberto Z

13 janv. 2020

A very informative course, getting more intense every week.

The professor goes through the statistics needed to understand end evaluate linear models using stock data and at the end it guides through building a daily prediction for SPY.

The only drawback are that the video might look short, but they are dense, and sometimes the professor use different names for the same concept, leaving you to connect the different names, e.g. Error ≈ Residual.

par Shaqil B S H

22 juin 2022

I found this course good for beginners in learning Statistics for Python programming, fairly there is a lot of information to digest. I'm content with the lessons and excercises for being very comprehensive, as well found the discuss forum helpful for sharing mistakes, thoughts and solutions.

I would reccomend this course to those who wish to understand the applications of stats in programming, or to expand their understanding of it.


par Yaron K

26 janv. 2019

A short course that shows how to handle time series data, run a multiple linear regression on it, and evaluate the results. This is only an introductory course, and as such it is clear and concise and thus deserving of 5 stars. However it only touches the surface of Python, statistics or trading. As for trading - before risking Real Money - it is strongly advised to learn much more on the subject of stock markets.

par Param D M

25 juil. 2021

I​t was an awesome course and learned a lot from the instructor. One thing i would suggest for those who are taking up this course is you should have a basic knowledge about stat and python libraries because course itself didn't told much about those things from scartch, overall the content and the way instructor had arranged this course is good and informative in my perspective. Thank You!!

par Joao S

12 oct. 2020

well, I expected the course to focus more on specific forecasting algorithms. But at the same time, I realized and learned how a solid base on statistics is fundamental, mainly for interpretation. It was an interesting surprise, even if it wasn't what I expected it ended up surprising me in a positive way. I just think the last week has become very information-dense, but overall, I loved it.

par Sandeep M

26 avr. 2020

Learning Python for statistics and its power through real life examples of Stock markets maintains the interest in learning uninterrupted. Thanks to Prof. Xuhu Wan for making the learning so interesting and simple- minute details of both, the Stock market and Python, I owe all my knowings of market and trends to him for simplifying the most confusing statistics in the world.