Complete Time Series Analysis With Python (Udemy.com)

The instructor seem's to rattle through jupyter notebooks but will say something like "you can set that perameter to 0.8" but not give any rational as to why? Or the effect of a change to the setting. But overall it was a good brief refresher to my stats from uni on time series

The course contains useful information about the utility of various tools in modelling time series data in Python. I am positive that the concept will significantly enhance the quality of my work. The instructor has displayed depth of her knowledge of the subject and appreciable teaching prowess in her lectures of the course.

This course contains valuable information about utility of various tools in modelling time series data in Python. The concepts have vast opportunities for practical use. The instructor's knowledge of the subject is impressive and she drives home the concepts in the most effective way.

This is an amazing course which discusses the importance of various tool in modelling time series data in Python. The course has vast potential for practical usage. The instructor has total command over the subject and her delivery is impressive.

Excellent course on time series using python. The instructor has nicely included Deep Learning, Facebook's Prophet also. One Final graph with a comparison of all the models (ARIMA, LSTM, Prophet etc) would be nice to have.

I would have like more Multivariate Forecasting examples. A majority of the lessons were based on one variable, but in the real-world most problems are multivariate. There was also a lot of time spent on different forecasting methods. I would have liked a deeper dive on just a few methods, instead of a shallow look at many methods. Some Python packages that were recommended were no longer available. Unfortantely the "why did i add this line of code" was really lacking sometimes, their would be code added with no explanation of why it mattered, and even the code in the video was sometimes cut off because it scrolled too far to the right.

The subject of the course is incredible important in many professional areas, and this course includes plenty of techniques and examples that helps to understand how implement them in real problems. Although the instructor describes in details each piece of code she uses in her lectures, I think I can be improved if she includes more explanations about the reasons of the code. In contrast, I asked tons of questions and always they were fully answered by the instructor. The above notwithstanding, if you have some experience on the field and you really want to learn, you will find this course useful for sure.

I like the systematic approach taken although the instructor is spending too much time on the basics. Time series is an intermediate level topic so students are expected to know the software in question.But I like the ML implementation. That is very current thing

The course is very comprehensive. It starts with Python data science basics and moves to basic time series models such as ARIMA and beyond. The hands-on examples are a plus. Will benefit from more financial examples

I am really enjoying the course. Very useful resource on time series with Python. Covers the conventional stats and ML approaches. I will now enroll for the finance course