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

4.4
stars
4,043 ratings

About the Course

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....

Top reviews

RH

Jan 4, 2024

It is an excellent course to apply statistic, probability and python methods in financial modelling. I would like that each section had resources to study statistics concepts related to the videos.

EJ

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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26 - 50 of 916 Reviews for Python and Statistics for Financial Analysis

By George Z

Mar 26, 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.

By Michael K

Oct 19, 2020

Tricky accent at time but great content and absolutely super Jupyter notebooks. The presentation looks cheap but this is one of the best finance/python starter courses on coursera.

By TJ D

Jul 5, 2019

The videos in this course are exceptional and very interesting. The Jupyter notebooks provide a good template for applying the methods and techniques.

By carlo

Mar 23, 2019

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By Robert P

Jun 11, 2023

Code does not work as well as it is outdated. No explanation on how to use the Jupyter notebook either. Leaves a bad taste in my mouth just thinking i had to waste my time with this when instead i learnt much more from youtube trying to fix this broken, outdated code of theirs

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 AJAY M

Feb 17, 2023

I would be happy to provide a review of the "Python and Statistics for Financial Analysis" course on Coursera.

Overall, I believe this is an excellent course for individuals who want to learn about using Python for financial analysis. The course is presented by the instructor who is an experienced data scientist and financial analyst, and he explains the concepts in a clear and easy-to-understand manner.

The course covers a range of topics, including statistical analysis, time series analysis, and asset valuation. The course also teaches students how to use various Python libraries for financial analysis, such as Pandas, NumPy, and Matplotlib.

One of the things I appreciated most about this course is its practical approach. Throughout the course, the instructor provides real-world examples and exercises, which allows students to apply what they have learned in a meaningful way. The course also includes a capstone project, which requires students to use their new skills to analyze real financial data.

The course is well-structured, and the lectures are organized in a logical and coherent manner. The course materials, including the lectures, readings, and exercises, are all well-prepared and presented clearly.

By Yash U

Jul 25, 2023

The Python and Statistics for Financial Analysis course is a great introduction to the use of Python for financial analysis. The course covers a wide range of topics, from basic Python syntax to more advanced statistical concepts. The course is well-structured and easy to follow, and the instructor, Prof. Xuhu Wan, is clear and engaging.

One of the strengths of the course is the hands-on projects. In each project, students are given a real-world financial data set and asked to use Python to analyze the data. This gives students the opportunity to apply the concepts they have learned in the course and to develop their problem-solving skills.

Another strength of the course is the use of Jupyter Notebooks. Jupyter Notebooks are a great way to combine text, code, and visualizations, and they make it easy to share your work with others. The course uses Jupyter Notebooks extensively, and this helps students to learn how to use this powerful tool.

Overall, I would highly recommend the Python and Statistics for Financial Analysis course to anyone who is interested in learning how to use Python for financial analysis. The course is well-designed, engaging, and informative.

By Antonio C

Feb 26, 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

By Harald M

Jan 20, 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.

By Mike H

May 13, 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!

By RAFAEL L V

Sep 9, 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!

By Nikos B

Mar 20, 2023

The course is not an introductory level. It requires a solid background in probability and statistics: random numbers, frequency, sampling, probability distributions, sample statistics, hypothesis testing and prediction modeling. In the second part, it teaches several python methods of doing statistics and gives more focus on data literacy than mathematics. The final part is some financial applications in time-series analysis of daily return of a stock, statistics of stock return and two important measures: Sharpe ratio and maximum drawdown. The course is a good comprehensive module in the statistical use of something and not teaching you statistics.

P.S. There are some missing links in the questions. Python needs some update.

By John Y

Apr 28, 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.

By ANJALI K R

May 9, 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.

By Festus k C

Sep 12, 2023

It has been an exciting journey in my studies. I have been exposed to several real time data and skills which have been added into my library of knowledge. The journey and adventure has been insightful which I also hope to continue learning in building and broadening the scope of my studies. Python and Statistics are among the powerful areas where the Financial Modelling and Machine learning heavily depend. The instructor has been so amazing with his well thought skills. I thank Coursera for the opportunity of learning. Cheers!

By Tim B

Dec 1, 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.

By Matthias H

Aug 27, 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.

By Christopher S C

Jan 1, 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.

By Shuhong L

Feb 7, 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.

By Sumedh K

Aug 11, 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.

By Tobias T

Jan 22, 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.

By Harshvardhan S T

May 1, 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.

By Facundo M L

May 18, 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!

By Charles P

Mar 23, 2024

First thanks a lot for making this class available to everyone, I enjoyed the class as it's very straightforward and directly applicable to trading/financial markets. It also used some theoretical skills from uni directly to the financial world and it was really well explained. There was some small mistakes along the way given different version of python and I had to look up some things online to understand but overall the class was really great so thanks again