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Back to Practical Time Series Analysis

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1,589 ratings

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!...

SS

Apr 6, 2021

It is a very good course which builds on the basics of time series and also covers more advanced topics like SARIMA. The course contains ample examples which helped me better understand the material.

SA

Jan 23, 2020

Excelente, uno de los mejores cursos que he tomado. Lo más importante es que se practica muy seguido y hay examenes durante los vídeos. Si hay un nivel más avanzado de este tema, seguro que lo tomo.

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By Matteo B

•May 25, 2020

This is a fantastic course, and I would recommend it to everyone that is interested in Time Series Analyses. After finishing the 5 week program, I can confidentially say that I feel comfortable to start tackling TS projects and build some forecasting models.

However, I deduct one star because the learning curve is very steep and could/should be supported more through graphs and examples, especially in the earlier part. This can be frustrating, especially for people without a very strong statistics background. My best advice for now is to keep going, many concepts become clearer in later lectures.

Overall, this course is highly enjoyable (for a statistics course on R) and I do recommend it to anyone that wants to explore the fascinating world of ARIMA models and time series.

By Jose L A

•Nov 18, 2018

The course gives really useful skills regarding time series analysis, but it seems a little bit forgotten by the authors since some links in the during the course are not working anymore ( for instance the link describing whether a seasonality is addictive or multiplicative "http://www.forsoc.net/2014/11/11/can-you-identify-additive-and-multiplicative-seasonality/". Also,there are time a future content is presented before the class in some questions, as is the case the moving average week where there is a question regarding auto regressive process, a content present in future classes. Besides those points, the classes and material are really helpful, and i can say that this skills learned will sure be used in my professional life

By Carlos R P G

•Jan 8, 2020

A very solid introduction to time series analysis, recommended if you have understanding of probability and statistics concepts.

I have seen some complains about the course not being practical enough. The practice comes at the last third of it, and this is as it should be. The SARIMA model is composed of 4 different models (S + AR + I + MA), if you don't understand them independently your chances of doing anything useful with it are slim.

I would have liked it to be more language agnostic since I use Python. The statsmodels module has all the time series analysis tools that you need, and allows to load R datasets, albeit not all of them. The rest you can find fairly easily googling.

By Stefnir K

•Dec 29, 2019

This course will teach you many of the concepts of time series analysis. It's a good course that is clearly taught by experts in the field and it is no lesser than any course I have taken at a university level.

The problem with him is that the lectures are dry and feel outdated, they are not bad in any way just two professors with a webcam and slides. The second problem is that the tests are a bit easy and you can pass them without understanding by just trial and error.

Overall I recommend this course for those that have little or no background in time series but would really like to dive into this topic. I also recommend at least 1-2 years of Bs in Eng or Sci.

By River B

•Nov 25, 2019

An excellent introductory course on time series analysis. It has an excellent blend of theory and practice and everything else became intuitive once you studied and gained intuition for the math. Some of the lower rated reviews mention too much theory, but I feel it was imperative to fully understanding the course and am glad they included it. Completing the entire course felt rewarding.

I docked one star because of the sloppiness of some of the slides and equations. Some of the examples don't work either. I enjoy William's videos as his pacing is good, but a lot of times Sadigov tries to rush through the slides as fast as possible.

By Marc-André C

•Apr 21, 2018

Well built class. I especially enjoyed the inclusion of written material, which I find easier, faster and more enjoyable than videos usually. The material itself is well constructed and the professors are clear. The low point for me comes with the intended audience of the class. At first glance, it is directed toward professionals that have already some familiarity with time series. While I could follow the course independently, I had to rely on other resources to gain intuitions on the concepts. I still don't consider that I could explain the material that I learned as well as I wish I would.

By Derek H

•Jan 5, 2020

Good introduction to time series analysis, covering the standard curricula of discrete-time stochastic processes, useful statistics, with some additional work with R and some introductory-level theory. The course is not especially rigorous and the quizzes are not hard, but as an introductory course for a person new to time series but with at least partial undergraduate mathematical background, this is a good start. I mostly read the slides to learn the material, as I prefer to read material on my own, and the slides were informative and easy to follow.

By Joseph H

•Feb 14, 2021

Good introduction to the fundamentals of MA and AR processes, the ACF, PACF, etc. I would have appreciated more applications, more examples showing how these tools are actually used in the real world. Suggestion: Add a week to the course where you take us through several "messy" real-world examples. For example, what are a few key research articles that have used the methods of this course and found REAL INSIGHTS about the studied system? Walk us through a few key real-world success stories of using these methods, from the research literature!

By Jerry H

•Jan 11, 2019

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.

By Sian X

•Aug 9, 2021

The two instructors explain everything crystal clear with cool mathematicians style which I enjoyed a lot!! They definitely deserve 5 stars! The 1 star I took away is because Coursera did not set a good expectation to this class, because of which I'm quite frustrated with how much maths i need to deal with and how less practical it is compared to my 7 years of experience in industry. Though after taking the course i have deeper understanding of the mechanism happening behind R existing functions - thanks to the two great instructors.

By Christian B

•Dec 29, 2019

I think the course is very helpful and you learn how to perform time series analysis. In the last chapter I was missing the motivation for using tripple exponential smoothing vs. the former SARIMA model. When would I use what? I give only 4 starts due to week 3, where many complained about, and I would agree, that the motivation for the mathematical construction of the Yuri Walker equations is unclear and the lesson itself is a bit confusing. However, week 4 is then way better, when using the matrix notation and concrete examples.

By Anisha S

•May 6, 2019

After coming towards the end of the course, I have changes my perception about the course. It is a great course to learn Time Series Analysis. Though it has some advanced theory and derivations in certain lectures, it has lots of practical exercises as well to perform hands-on. It gives good understanding of time series concepts and different models associated with it. I would recommend this course. I would recommend the instructors to add ARIMAX and multivariate time series analysis in the course as well.

By Joel A

•Mar 25, 2020

There are some inconsistencies with notation. The quizzes are much too easy and the code/problems are basically given to you. I would say this is a good introductory course to see if you have any interest in the subject. There is some good theory development in the weeks covering autoregressive and moving average models. I did learn some of the terminology and methods for time series analysis that will allow me to go into more developed sources with a basic intuition of some simple processes.

By Jean-Marc S

•Jun 4, 2020

Interesting course, however, if you don't already have a STRONG background in math and statistics, you will get lost after about half of the first week! Some videos are just throwing formulas all over the place, without really understand what they are doing. Some are more detailed. Overall, interesting. But I think I got only 60% of the knowledge. Might have to retry later, or maybe do a different one. A glossary document will have been a nice to have (MA, AR, E, V, ACF, iid, ARM, AIC, etc.)

By Igor U

•Dec 7, 2019

I liked the emphasis on implementing the theory on data within R as this knowledge is directly transferable to real life application. A good way to go from 0 time series analysis knowledge to a base that can be the starting point for further learning. I noticed occasional errors in the material (EG. one quiz question asking for lambda() whereas it meant gamma()), but nothing that significantly takes away from the learning experience. Thank you for providing this quality course for free.

By Yaron K

•Nov 7, 2020

The course teaches the mathematics behind SARIMA - Seasonal Autoregressive integrated moving average, and SES - Simple Exponential Smoothing. If you want to understand the mathematics behind these methods for time series analysis - this is a 5 star course. If you want examples of programming them in R - 5 stars. If you're looking for practical examples - there are practical time series examples in the second half of the course - but not many.

By Evans M

•Aug 25, 2021

It was a great course. It gave me a firm foundation in time series and its application to forecasting. While some of the lectures were quite "mathy", I hanged in there and at the end day everything made a lot of sense. I now have a clear understanding of the underlying principles and I can explain the inputs and outputs of the models a colleague in my own words. I would say it was a worth investment both in terms of time and the $40 bucks!

By 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.

By 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.

By Abhidnya V P

•Aug 20, 2021

Good course if you need to gain a general idea about time-series models, and forecasting concepts. I was afraid to hear words like 'ARMA', 'ARIMA' models in the research papers. After this course, I know what those papers talk about when they refer to these terms. If you need to apply this knowledge for some project, you might need to practice more than the practice quizzes in the course.

By MBOUOPDA M F

•Apr 29, 2020

When I started this course, I wanted to get familiar with Time series analysis, particularly the forecasting aspect. I am happy to say that I am satisfy. The explanation are very clear and I was able to follow without any prior knowledge in time series analysis. The only problem I observed is that the materials are out of date. In fact, some links do not work anymore.

By Lijie T

•Mar 31, 2018

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.

By Dziem N

•May 10, 2021

A gentle introduction into this important area of Data Science & Analysis. The lectures take care in explaining the salient points of the topics and provide a lot of practical insights (tips & tricks) which enable students to carry out these analyses themselves. The qualifier "Practical" in the Course Title is well-deserved.

Thank you very much...

By 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.

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