Un curso con una perceptiva muy refrescante en cuanto a los conceptos técnico-estadísticos y sumamente prácticos. e incluso baratos, de implementar dentro del mundo de la inversión. Muy buen trabajo.
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.
par Harald M•
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•
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!
par RAFAEL L V•
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 ANJALI K R•
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•
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•
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•
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•
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•
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•
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•
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•
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 Bernardo A•
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 João A A•
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•
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 Yaron K•
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•
It 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•
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•
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.
par karim a•
vraiment avec une immense joie que je vous écris ce message, merci à toute l'équipe qu'a su faire preuve de professionnalisme, vraiment c'est été un contenu incontournable, qui va m'aider beaucoup de mon travail de recherche, je vous encore une fois pour ce cours et je vais rester fidèle à tous vos cours en ligne.
par Yen-Wen Y•
It is very practical, and you can really achieve something within short time, but the pace is a bit fast, and you do have to do some additional research in order to follow up. You get insight in finance, statistics and python. But it is not a pure python course, so you would want to find something else if you want to learn particularly python.
par Hei T Y•
Good course! It demonstrates how python can be applied on financial analysis. Better to have some prior knowledge on python and statistics before taking the course because this course seems to aim at showing the relationship between textbook statistics and python in financial analysis instead of teaching you basic concepts from scratch.
par Karthikeyan V•
very good. more description of each of the words, atleast definition would be helpful. Use a white board to draw a picture or show something relevant to the words/subject. I don't know, this correct approach or not.
I did not buy the certificate, It cost a lot $50. If it is $5. I would consider.
par Lorenzo P•
A complete course about Statistics and Econometrics tools for finance. I appreciated Jupiter notebook that made it very useful and full of practical applications. The level of the course is bachelor's degree. Recommended for whom who have a previous experience with statistics and wish a refresh on it.
par Andrii T•
Due to the fact that it's the first course I've completed on Coursera, I can't compare this one with any others here. But I should admit that it gained me a lot of insights on my way to study Data Science. That's how the statistics should be taught - only with the assistance of proper software.