some mistakes in the handout, but still learn lots of useful knowledge and skill from this class.

Good course to learn the basic concepts about time series. In my opinion there should be more practical exercises. They force you to better understand the theory and are always a good idea to really master any subject.

Great content

The course met my expectations, which was to develop basic skills and tools to better understand time series as a jumping off point for some of the work I am doing. I found the practical examples (e.g. coding of the solutions) to be most helpful for my learning style. Also appreciate concept development thrust, to help better understand the applicability and pitfalls of the tools. That being said, I didn't particularly find some of the mathematical derivations helpful, given my bent toward the practical application of the tools and concepts.

I liked it a lot and it helped me a lot to understand the topic that I am going to use in my thesis.

It has a little messy some classes and topics so they should revise some videos.

Great course, good balance between theory & practical applications.

For some lectures, the slides are not provided (pdf notes are provided instead). I would preferred to have the PDF sliders of the Power Point as well.

It's a course with a very well load of math content. In my opinion, it should include more practical cases focus on give to students a hands on feel of what happens by under all the math explained here.

The course is really nice and delves deep into the underlying math behind the forecasting technique. The course would have been even better if they would have talked about time series forecasting with predictor variables.

Chapter 3 needs work. Everything else is great! Good course overall.

Overall, this was a really great class. I have a good grasp now for the basics of modelling time-series and producing forecasts (using ARIMA, SARIMA, Smoothing with Holt-Winters). I also have an understanding of the tools used for analysing time-series (autocorrelation, partial-autocorrelation).

The course is a good mix of theory and practice. I haven't taken a stats class for a long time; however, the first week was more than enough to refresh my memory. Really, only some basic stats knowledge is needed (mean, covariance, correlation). There is also quite a lot of usage of the geometric series. However, a lot of time is spent reviewing this topic later (week 3, I think). The course is done in R, but the usage is so small that anyone with any experience in programming will have no trouble. I actually had no experience with R before this course, and I finished the course with only a little additional experience.

My only complaint is that the course could use some minor maintenance. One of the weeks (maybe 3?) has a section of duplicated notes, but I'm pretty sure that the section with duplicated notes could be deleted. Most of the pdfs have the wrong week in the header (likely a new week was added after the course was released). There are also several quiz questions with incorrect values (before taking a quiz, I recommend scanning through the forum to find known problems). The instructors do occasionally post in the forums, so that gives me hope that the course will not be abandoned.

I think I need support on the very last week, namely, week 6, on the very first quiz. I don't understand the answers on how they were derived but I was able to get the answers by repeating the quiz.

I thought everything was had a great layout. I found the proofs dry, but necessary.

A good course to start up with time series forecasting. The code meets its objective of teaching practical time series analysis. Though, a little more theory on the same would be appreciated

The instructors adopted a very practical approach to teaching the core concepts in Times Series. They did a great job using examples to analyze the data and explain the concepts. However, I do think the lectures are somewhat disorganized in some chapters so that some concepts are used before they are mentioned. Overall speaking, this is a great class.

Very Good Course, Thanks for clear explanation.Comparison & Selecting the best model for a given dataset with train, test split would have given practical approach and implementation in real time project.

The lecture ended just where it has become interesting.

Very useful introduction course to Time Series

Course is good and intuitive and people not from non-mathematical/non-engineering backgroung may take more time in week 2

This is a good course, but it is too focused on R routines and leaves some practically important questions unanswered. Specifically, no algorithm is provided for fitting parameters of MA models.

Answers to assignments could be more elaborate

A very good introduction to time series analysis. Provides some theoretical fundamentals and explains how to implement it in R.

Great course for info about time series.

Some parts (especially week 3 and 4) could be less mathematical.

Should emphaise more on identifying the ranks of the models, for example - keep those questions in the quizes.

Some quiz questions felt too easy :)

Good practical overview with lots of exercises

It was a really good course, very informative and well explained. Only I could find minor mistakes especially during the test where it was difficult to observe the figures or the code did run smoothly. I highly recommend it.

maybe useful, but this course worth listening