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Kursteilnehmer-Bewertung und -Feedback für Practical Time Series Analysis von The State University of New York

4.6
674 Bewertungen
179 Bewertungen

Über den Kurs

Welcome to Practical Time Series Analysis! Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics. In practical Time Series Analysis we look at data sets that represent sequential information, such as stock prices, annual rainfall, sunspot activity, the price of agricultural products, and more. We look at several mathematical models that might be used to describe the processes which generate these types of data. We also look at graphical representations that provide insights into our data. Finally, we also learn how to make forecasts that say intelligent things about what we might expect in the future. Please take a few minutes to explore the course site. You will find video lectures with supporting written materials as well as quizzes to help emphasize important points. The language for the course is R, a free implementation of the S language. It is a professional environment and fairly easy to learn. You can discuss material from the course with your fellow learners. Please take a moment to introduce yourself! Time Series Analysis can take effort to learn- we have tried to present those ideas that are "mission critical" in a way where you understand enough of the math to fell satisfied while also being immediately productive. We hope you enjoy the class!...

Top-Bewertungen

JM

Mar 21, 2019

This was a very good and detailed course. I liked this course for two reasons mainly:\n\nIt started from the basics of timeseries analysis, covering theory and secondly it took me gradually to r.

LY

Aug 03, 2019

A nice course which is practical as the name said, it balanced the portion of theories and practices. I used to not familiar with this topic, but now I consider myself much more familiar.

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151 - 175 von 178 Bewertungen für Practical Time Series Analysis

von Yash G

Mar 25, 2019

Amazing course

von Hany N

Apr 11, 2019

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.

von Siddharth M

May 28, 2019

A very thorough course covering almost all the topics related to time series along with the math involved. However, the explanation for the math involved was not very elaborate and easy to understand. A lot of parts were skipped in the explanation. Moreover, the examples taken to explain were simpler, rather than taking a tough example and covering all the corners. Overall, a great course but not for a layman.

von David S

Jul 01, 2019

Little fast and some place in the middle when they started talking about inside the unit circle. May need a little refresher on that. Otherwise I really appreciate this type of material being available.

von Supakrit N

Jul 09, 2019

Great course with clear description but the sound of mentor is almost monotone making me feel some sleepy

von Luiz C

Jul 15, 2019

Exercises and Quizzes could be more complex

von Ron C

Sep 09, 2019

Professors obviously know their stuff and work to outline all the math fairly logical. The title, "Practical Time Series" is a little lost on the actual workload. I am finishing week 3 and I have yet to find anything 'practical' about the course. i'm very intrigued about the math, it is interesting and challenging, but i felt like the discussion in week 1 about all of the data sets we were going to use was a tease.

I would be better able to absorb (not just learn it long enough to ace the quizzes) the material if for each concept there was a practical application of the concept to one or more of the data sets that were made available to us. Because we don't, I often find myself in my own head, searching for applications, and thus not fully paying attention to the videos, which then I have to go back and watch multiple times.

von Parikshit A B

Sep 11, 2019

The course is well paced and covers a lot of material. It could have been better structured though.

von Andrew W

Aug 26, 2019

Well presented material and relatively easy to follow.

von Arthur B

Sep 29, 2019

A very good course that covers both the theoretical Mathematics and the practical implementation in R.

I feel more confident now on time series analysis. I learned how to do forecasts, to interpret PACF and ACF and understand ARIMA and SARIMA.

A few small sections in the video went too quickly, but the material overall is excellent.

von Neil T

Oct 02, 2019

Classic intro class. But it will be better to explain the difference between exponential smoothing and SARIMA and why we need the first one.

von Ramprakash V

Oct 15, 2019

Helpful for the ones who really want a strong math foundation for Time series.

von Kaumba C

Oct 14, 2019

Very helpful

von Lance D

Oct 20, 2019

Course provided solid understand of Time Series Analysis. I wasn't expecting to see so much math, but glad they included it. Recommend you study up on Time Series math before taking course. All of the math was converted into R algorithms for you and/or R function calls to packages that supported the concepts. I was immediately able to start applying my knowledge to my day job as a Software Engineer / Data Analyst.

von David R

Nov 09, 2019

I'm in week 5, and I think that this course is interesting and you learn from it. However it is done in a somewhat sloppy manner, to my taste.

My biggest problem is the notations and equations are a bit of mess. Beta's in one equation are replaced with phi's in another (sometimes in the same "lecture" slides) or theta's - there's just no real coherent notation. The formulas are brushed through, and they contain mistakes (a product of this sloppy notations), e.g. pi(beta) is missing the beta (which is what it depends on! week5, ARMA properties and a little theory). The R code is also sloppy, for example you see them setting variables in the first cell, and then never using them in the next cell. Or calculating variance using a cumbersome call to an acf function telling it to bring back the autocovariance, and taking the first term. TL;DR - It's just sloppy.

There are no exercises, but the quizzes contain some code you can run. Not enough for really drilling the material into you, though.

In general, I think this course could really improve, and I would like to see it do so. As a general introduction to the topic it might be decent enough.

von Paulo H S V

Nov 10, 2019

It's a great course and it will give a great overview of the main forecasting techniques. However, the course is not THAT practical, since there were a lot of lessons talking about the theoretical concepts instead of coding. If don't have a good understanding of Algebra, you might get lost throughout this course

von Miguel L

Sep 05, 2018

Overall, it is a pretty good course: in just a few weeks you are introduced to a satisfactory level of time series analysis with R even if your background in R and/or statistics is not that high. I have personally missed some more depth (even if optional: for example, providing additional optional readings, or creating an honours track with extra difficult assignments for motivated students). Instructors are pretty good but they should make an extra effort to be clearer and not to speed up too much: some more additional videos or just more time for each video covering the same content would be better.

von Pablo C T

Oct 14, 2018

Overall, this is a good course for beginners in time series analysis.

However, I wish they had go beyond the basics. I missed more advanced content, discussions between different forecasting techniques, multivariate forecasting...It is pretty basic.

von Maria B

Oct 19, 2018

The content was great, but I'd have liked to see more practical exercises.

von Juan M G H

Sep 26, 2018

On other courses I received feedback on the forums in a prompt manner from the instructors, here none of my questions have been answered.

von Mark H

Jun 27, 2018

Would have loved more work with the ready made packages, I feel like I still can't master using them in R, although I did understand the material.

von Artem M

May 18, 2018

Contents of the course are very good. It provides a compact introduction to the most important statistical methods for time series estimation. Nevertheless, there are many mistakes in slides/exercises, necessity to download datasets instead of using predefined ones, and a great number of time series libraries to download when we could just use 2 of those, which is ok, but I took 1 star for it. The other star taken was because I think the course could still include more information on the theory of time series (yes, I understand that the name is PRACTICAL time series, but still), and more meaningful exercises. Most of those were pretty trivial.

von Heberto S

Apr 01, 2019

There was not a good intuitive and more visual explanations of the principles behind the techniques.

Given the proposed 'practical' nature of the course, it would be better to explain any concept by using concrete every-day examples than preceding them with a elaborated mathematical reasoning of the equations used.

von Richelle S A

Jul 21, 2019

It was a nice course, very informative. But week 3 simply had way too much matter in it in comparison with the previous 2 weeks which makes it difficult if you've set a timetable. Also, week 6 had poorly maintained data availability, and missing code. Lastly, the professors are absent from the discussions. There are unanswered doubts from longer than a year ago.

But if you dedicate enough time and effort, this course is pretty good.

von Herman d V

Nov 06, 2019

Very interesting course. For a 'practical' course, I did find it rather theoretical. Also, some links to downloadable data are missing and there are some small errors in the R scripts that are offered. Nonetheless a good course, I learned a lot!