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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!...

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.

Jul 17, 2020

Easily one of the best time-series courses online. Although it says "practical", there is plenty of good theory to back up the practice and at the same time not overwhelming or distracting.

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von Luiz C

•Jul 15, 2019

Exercises and Quizzes could be more complex

von Mohamed I

•Jun 15, 2020

need more programming examples and trials

von Yeliang P

•Aug 14, 2020

Quite lucid, a little bit too simple

von NANDAGOPAL S

•Jun 02, 2020

Still more practical examples needed

von Igor R

•Mar 16, 2020

A little basic, but fun and useful,

von Koustav M

•May 02, 2020

Great help concept and R code wise

von Udit G

•Mar 02, 2019

Good, but can be more extensive.

von DropRooster

•Mar 08, 2020

Great for beginners

von Yash G

•Mar 25, 2019

Amazing course

von Prateek G

•Jan 01, 2019

Great content

von Kaumba C

•Oct 14, 2019

Very helpful

von Wim

•Jun 02, 2018

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von Daniel M d C

•May 30, 2020

The course is a good opportunity to learn and/or review basic concepts on time series modeling (e.g. ARMA, ARIMA). They are presented in a way that ideas are easily understood, but also covering enough detailed aspects. I really enjoyed lectures of Professor Sadigov as he usually derives all of the formulas presented.

However, there are many things in this course that I would urgently improve. Content is not properly sorted, so you can find concepts being mentioned before being introduced or concepts being introduced twice. Moreover, I have encountered errors in both slides and quizzes. Most of them had already been spotted by other users in the forums, but they have never been corrected. Indeed, course has not been reviewed for a while, so you will often struggle to get the data used in the lectures as links provided are no longer valid. Quizzes are also very simple, most of the time.

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 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 Sharon M

•Feb 28, 2020

While this course was pretty thorough, it was way too mathematical and not nearly as applied as I would have expected a 'practical' course to be. It was also extremely frustrating that a large proportion of the forum messages went unanswered - I've never done a Coursera course before where there hasn't at least been a research assistance answering questions. You really had to try to follow everything yourself, and if you had a question, you had to find the answer yourself. A bit disappointing.

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 Lyla F

•Jan 24, 2020

It's decent for what it is - a course trying to balance theory with practicality. However, it uses R for the target implementation environment. That's fine, but as a matter of taste, I prefer python. Therefore, for me, the practicality aspect of the course wasn't the greatest, and that was its main selling point.

von Arman A

•May 18, 2020

It is in R, making it rather limited for applications in industry, however using Python's statsmodel you should be able to keep up with the notes.

I was expecting a lot more theoretical explanation of the concepts rather than just demo'ing some R code and fitting some libraries to data.

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 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!

von Emanuel N

•Mar 09, 2020

While professor Thistetlon gave the classes in a way that kept my attention,Prof Sadigov wasn't so good at it. Clearly he know a lot but not as a teacher.

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 SAKET M

•Apr 18, 2020

Instructors are good but as per the title this is not more than 30% practical Time Series Analysis

von Maria B

•Oct 19, 2018

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

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