Learned a lot, however, it gets complicated really quickly. My intention for this course was to learn more about how Python is used in business analysis as this is something I am planning to do for college. I feel that it would be greatly appreciated if even basic statistics tools would be expounded more on as I did not really know these and it took a toll on my progress in this course. I would also appreciate if the labs were more hands-on, meaning that we would be the ones to build the code and applying our understanding of the videos. Although in certain labs this is done, some of the labs would just let me run the code that was already pre-typed. I think that allowing students to apply their understanding would allow them to remember more the lessons provided by the course.

I learned a lot and I greatly appreciate Mr. Wan for creating this course as it will certainly help me in the future.

A fine introduction to the use of statistical models for finance (stock trading), showing its implementation in Python. It is NOT a course in either Python or Statistics but shows what one should learn. Alas, it does not give any pointers as to where to go to delve deeper into the needed statistics (nor trading, for that matter). It contains a fair summary explanation of linear regression models, but the recipes for their evaluation are discussed way too briefly.As for Python, it uses 4 common important libraries and directs the student to the corresponding sites. It gives no explanations as to the kind of structures being manipulated. The Jupyter notebooks are well set-up for practice.

The course provides an overview of how to build a quantitative trading model. However, the instructor does not go into details while either introducing python functions to someone unfamiliar with the language or talking about statistical concepts. I could follow the code based on my background in other programming languages.I will be following up this course with other courses that go in depth on both the programming and statistics front.The Jupyter notebooks are quite helpful and I will be using them for future reference.3.5 would probably be a more honest rating of the course but I don't think the course could have taught the learner more given its length.

This course shares a lot of info on how to use statistical analysis formulas like RMS, p-value, std. deviation, etc., and how to apply this knowledge using data modeling in a really easy way. There are some small hurdles to get over when taking the quizzes as some of the answers can be interpreted in multiple ways. out of the 4 quizzes I took, i attempted at least all of them 2 to 3 times. Not sure if I failed to absorb the knowledge well or if the goal was to go back and review the course material with a finer comb, either way, I found the course helpful and useful. I'd recommend it to friends and colleagues.

Good for what it intends to provide, namely a quick introduction to the topic, but it doesn't go very deep.

It is slightly annoying that there are plenty of typos and grammatical mistakes all over the Python code and the quizzes, which could easily have been avoided if either the author had somebody proofread everything quickly, or if Coursera had any type of quality control.

Nevertheless, coming from another programming language, I did get out of this course what I wanted, namely a collection of all the basic Python commands for this kind of analysis. So thank you for providing this course!

I would like to express my gratitude to the instructors and staff of the Python and Statistics for Financial Analysis course for their excellent teaching and guidance. This course has helped me to learn the fundamentals of Python programming and statistical analysis, as well as how to apply them to real-world financial data. I have gained valuable skills and knowledge that will benefit me in my future studies and career. I appreciate the opportunity to learn from such experienced and knowledgeable experts in the field. Thank you for making this course enjoyable and rewarding.

In general a satisfactory course and not too to follow through. It is focused more on the stat side than finance which I kinda have a mixed feeling toward. Professor could probably have done a little better job on explaining the meanings behind the formula but for the most part it is not hard to figure it out yourself by searching or reviewing the materials a few times by oneself. I also feel this course is a bit short, and if in the future it can try to cover more topics that will be awesome.

But hey I did learn stuff and am happy to have taken this.

First of all, I want to thank professor Xuhu Wan, as i have benefited a lot from the course, which not only broadens my knowledge of statistics, but also helps me familiarize with practical application of python. Overall, this is a well-organized, inspiring course worth recommendation, although it would be better if the pace is a bit slower and the explanation of the code is more detailed and thorough. I believe this course helps build my python skills in financial analysis, and hopefully this experience can help me earn my PHD offer.

This is an awesome course which takes you through the statistics for the financial analysis. The course needs some update to correct some broken links, inconsistencies. It requires some basic knowledge of statistics and python programming beforehand or study of these topics alongside this course, which should be made obvious to some learners who may be puzzled (I see in the forum that several learners were quite upset about some difference in expectation vs the reality which I think could be narrowed down).

A well structured course with a good base of learning in the first two weeks, I had a slight problem with the sudden leap in the intensity of the learning objectives in week 4 in comparison with the 3 previous weeks, but fortunately I went through it finely. I would like to thank everyone involved with this course. Well done!

Ps: You do not need to know how to use python to take this course, week 1 is a really good introduction even for the ones using python for the first time(just like me).

Es interesante, muchos comandos y cuestiones teóricas de los últimos temas se explican rápido y sin profundizar. He aprendido y revisado conceptos que ya sabía. Me queda la duda de como afecta el margen de la oferta y demanda al proceso de evaluar estrategias financieras. El uso de Python simplemente es una herramienta para explicar conceptos, no se aprende realmente a programar, aun así en la mayoría de casos es fácilmente entendible ya que todo sigue un razonamiento lógico.

The course was indeed helpful for my main goal to improve my skills using Python libraries to carry out mathematical / statistical caclulations.

One minor issue:

As I downloaded the notebooks for replaying them in my local Jupyter installation which is based on Python >= 3.6, I had to manually correct some statements due to changes in pandas, e.g.

pd.DataFrame.from_csv -> pd.read:csv or

pandas.tools.plotting -> pandas.plotting

mho it would be good to check for such issues

This course is more suitable for someone who has basic python knowledge. understand that there is a challenge with teaching programming languages via online platforms. It is quite difficult for the instructor to shorten the whole course into 4weeks material. Appreciate that the instructor and TA do spend time to answer student’s questions in the coursera forum. Candidate needs to spend extra time to view other sources to better understand the course material.

Thank you for your effort sir, I am grateful. Unfortunately, the refer links used in the quizes did not work for me, I lost a few points because of that. I am an electrical engineering student, I do not know much about statistics or finance, but I am familiar with python. I had to do a little research on the terms directly related to those subjects like quantiles, covariance, p value etc. But, you did introduce me to a lot of new things in that way.

Exactly the Course right for me, Very usefull codes and Analysis used in this Course. Only that am the code used was Pyuthon 2 and some of the codes are OLD, It will be good to update the Cousre Cataloge and Modinized some of the Codes Used. This Course should be updated and add additional Courses to makeup a Proffesional Certificate that will prepare students Financial Analysis Position. The Course was very Usefull for me.

A wonderful course to get an introduction into financial statistics and a few python basics. This helped me understand many things about prediction and trading strategies. However to truly understand how to code a financial trading strategy you will need a lot more practice than you get in this course.

I really liked the course and would recommend it to anyone who wants to learn more about financial trading and python!

Nice course with a lot of easy to digest code. Concepts are clear and coding tools are very practical. however there isn't enough emphasis on checking step by step that data manipulation is as expected. Very dangerous not to do that when promoting that one can use this method to create a trading strategy. Plus every trading strategy has to have a trading cost consideration - none of that here unfortunately.

-: some little mystakes, exercice level very low

+: large présentation that provide both python and core financial statistics skill within high level

Might need more time than expected, maybe twice, in order to code the exercice meanwhile watching the video. Cause the final exercice for each week consists just in changing some value. Not enough to know about coding. Except if you already properly know Python

Covered a lot of good content ultimately but the pace was slow and basic content in week one and progressed to very intense by week 4, felt more time should have been given to the week 4 stuff. A lot more emphasis given towards checking models/ best fits than necessarily building them. Also a few issues with subtitles, and confusing quiz questions that didnt always match to the workbooks given.

Great course overall. I've found that the learning curve and pace of the topics explained increases too fast on the last chapter. In my opinion, the last chapter (which I thought would be the most interesting and practical) was a bit fast and you get the feeling that was done in a hurry.

Great to gain tools to analyze data and financial/statistical techniques useful for any field.

This course is a good starter for you to apply financial analysis by using Statistics models with Python programming. If you have experiments in either programming or statistics, you will find lessons are quite easy to understand. I recommend classmates could take a look at some python plugins such as flask, yfinance. They are wonderful tools for further study.

The course was helpful and definitely interesting. The only problem I found was that a lot of pre-existing knowledge was required and I had luckily studied some of it but the course did not cover it, It would also be helpful to add more indicators to show what each variable stands for in the formula since I found myself forgetting and had to rewind.

Very good introduction in Financial Analysis using Python. In week 1 through 3 all concept are explained very clear, week 4, the most important week, is a lot of information in only a few video's. I wish these week was extended so these concepts could be explained with the same thoroughness as week 1 to 3. Overall I enjoyed the classes very much.

The course material is fantastic as well the teacher is knowledgable to tutor key concepts of stasttistics using python that can be applied in financial data modelling. However, some of the Jupiter notebooks don't work for questions asked in weekly tests. I think people may need some mathematics background to fully understand this course.

The course provides a very good learning experience. The course explains the various statistics that go into evaluation of stock data and further its execution using Python. The explanations could be bettered as there were many instances where pronunciations could not be comprehended. Overall the course provides a good learning experience!