Python for Time Series Data Analysis (Udemy.com)

This course about time series analysis with Python is definitely the most absorbing course I have ever met so far. The explanation is concise and clear. I used the concepts and tools learned from the course to analyze BCPI and BDI and get a ubique insight to help my investment. Hopefully the instructor can conduct more python-related courses.

The first sections are really perfect. Then the section 8 which is the longest and the most important misses a bit, in my opinion, more explanations about the theory and even more coding for praticing more and understand better the theory. Same analysis also for the last sections about Deep Learning and Prophet. But in its globality, this course is very valuable.

I appreciated this course very much. Sometimes it was a bit to fast for me and some explanations could be a bit more extensive (it would be much more helpful, explaining the shown mathematical formulas with own words instead of just reading the symbols on the screen). A tool that could help to explain the single methods (AR, MA) would be simple Excel spreadsheets with the respective examples. I created them by myself to better understand. On the other side, the course is accompagnied by extensive solution notebooks with many helpful hints and links. Regarding the results of the single coding examples, I sometimes was not able to reproduce the results shown in the course. Sometimes libraries have changed (e.g. Keras) and, as a consequence, the code had to be changed, too respect to the lectures but usually it was not a problem finding the solution on the web. Summarizing, for me this is a great five star course and I would take it again with pleasure. If the author would ask me how to further improve it, I would answer: by creating a stronger involvement with the used datasets and results of the single exercises would be my suggestion and not regarding the data as simple demonstration materials. In the sense of Antoine de Saint-Exupery: “If you want to build a ship, don’t drum up the men to gather wood, divide the work, and give orders. Instead, teach them to yearn for the vast and endless sea.” :)

Great course ! Jose knows what he's doing pretty well. Thank you !!! maybe there are times when I load the code and it won't work but whoever just new started this course don't worry! . learn to find till it works and u gonna feels really cool about it ! XD . about to take your My sql course later soon hehe

Great course...I learned a lot and am able to apply the various forecasting techniques to new time series data sets (eg, the current SARS/COVID-19 data). Installing some of the packages (ie, tensorflow and fbprophet) can be a little tricky, so read the installation documentation carefully. I made it through--so you can, too. I enjoy Jose's teaching style--everything explained in a straightforward, clear and easy-to-understand delivery.

Covering almost all topics and indepth explanations

Need more basics level handholding -- like how to upload excel data into the python workbook etc. also practical examples like currency forecasting for on annual basis

Good, what I expected

This course on time series analysis is simply the best you can get on the entire Udemy platform as of now. Most of the state of the art techniques have been covered in the relevant sections. However Facebook Prophet's section could have been detailed a bit more. Definitely, the course is worth pursuing for solidifying the foundations of time series analysis via python.

This course has very good coverage of forecasting techniques and manipulation of time series. Jose also explains the content clearly and makes an effort to answer questions. There are few hiccups in the Statsmodels portion of the course that generate a bit of confusion due to some functions that have been updated and deprecated, even if you run them within the conda environment activated, however if you are eager to learn this wont stop you.

Very well explained all concepts and their application on the notebook

Great explanation of ACF / PCF. Great explation of auto_arima and how the p,d,q and P,D,Q are chosen. Great notebooks and complementary lectures links