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 …
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Specification: Practical Time Series Analysis

58 reviews for Practical Time Series Analysis
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Price  Free 

Provider  
Duration  25 hours 
Year  2018 
Level  Intermediate 
Language  English 
Certificate  Yes 
Quizzes  Yes 
FREE
Jen –
I think it is really practical and useful
Kazantzidis C –
It was the first time I deal theoritacally and practically with Time Series. It is a perfect course for a beginer. In my opinion this course need some prerequisites in Calculus but even if one doesn’t have he can complete ther course. In addition this will be a stimulus to build the adequeate mathematical backround. Finally I would like to refer that just completing the course doesn’t mean that you have aquire the pertinent knowledge. On the contrary you have to do a lot of on the job practice with reference the material of this course. The real data for practice is the date every one finds in his occupation e.g sales , production and the like. To the Proffesors of this you I would to refer that in the update of this course it would be very good to include a Week with Regression with time series and some theorhy and practice of detrending. Thank Indeed.
Andrea B –
Excellent course with a nice balance between theory and practical implementation. It would be useful to have a more advanced subsequent course with the same features.
Andrew W –
Well presented material and relatively easy to follow.
RLee –
It should have included GARCH as well!
Ron C –
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.
Aishwarya A –
I loved the simple yet intuitive mathematical concepts that accompanied each lecture. Could have included a capstone project.
Parikshit A B –
The course is well paced and covers a lot of material. It could have been better structured though.
Maxim V –
This course is a perfect complement to Rob Hyndman’s book!
Supratim C –
Very monotonous lectures. They feel like a recitation of formulae.
OMOSALEWA M A –
Great course indeed
Arthur B –
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.
Ashok B –
Very useful course to establish the core fundamentals of time series data – which is very prevalent in real life. Instructors are really great and the quizzes are very well designed to reinforce the concepts.
Neil T –
Classic intro class. But it will be better to explain the difference between exponential smoothing and SARIMA and why we need the first one.
Juan A E G –
Excellent course for having basic knowledge for time series analysis.
Zhihua Z –
This course is very helpful with making all concepts and applications clear. Two professors explain each topics very clearly!
Kaumba C –
Very helpful
Tess P –
Love this course. Great theories and practical examples. Strongly recommended.
Ramprakash V –
Helpful for the ones who really want a strong math foundation for Time series.
chundarathil a –
Amazing course structure with apt information required.
Lance D –
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.
Lucia –
Pretty good! I enjoy the course very much.
Herman d V –
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!
David R –
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.
Paulo H S V –
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
Neel D –
Too much detail and outdated course
Manjeet K –
If you have the patience to learn time series with little knowledge of statistics, then this course is for you. Believe me, the course is really a “Practical” time series. Good course for beginners, I am satisfied.
Kanchan K –
It is a good course if you want to learn about the basic concepts of time series
Aniruddha B –
Good course for the beginner who wants to learn Timeseries problems
River B –
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.
Igor U –
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.
Ojithma G –
This course covered what i intended to learn, quizes were based on what we had covered so far, which is really good .
Christian B –
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.
Stefnir H K –
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.
Nicolas E H –
Excellent introduction to the topic, and practical examples easy to apply to new data.
Derek H –
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.
Somanadha S B –
Very unhappy with the course. Just completed it because I started it. Waste of time.
Carlos R P G –
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.
Alla E G –
Thanks
DELCIN M K –
Could’ve been more technical, with introduction to new machine learning techniques like RNN.
Taoufiq B –
Learned So many things
Sergio A –
Excelente, uno de los mejores cursos que he tomado. Lo mas importante es que se practica muy seguido y hay examenes durante los videos. Si hay un nivel mas avanzado de este tema, seguro que lo tomo.
Lyla F –
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.
Andrea P –
The course is exceptional. There are a few mistakes here and there in the material, but overall it is terrific. Recommended prerequisites to enjoy: basic linear algebra, calculus, basic statistics and probability course. Thistleton will make you learn the essential stuff with charming videos and readings.
Andreas Z –
This is the course for everyone who always wanted to know what all this ARIMA stuff is all about.
Marek D –
Great content!
Sanjeev G –
An excellent course if you are looking to get working knowledge of time series analysis. Basic working knowledge of univariate statistics will go a long way in making the learning easier. I would recommend it.
Aman G –
The course gets you started with building models of time series dataset in almost no time. Though course does not cover in depth theory but the course do really says that it is a “Practical” Time Analysis Course.
Eli R –
Time Series Analysis is done for one two reasons: [1] build a model quantifying patterns and noise and [2] forecasting. The two goals are very different. You can execute forecasts in R without understanding the underlying mechanism. To get a good grasp of time series forecasting you MUST understand how to model the time series and that is done with mathematics. COURSE GOAL and CONTENT: This course focuses on the mathematics of building time series MODELS. Forecasting is addressed lightly towards the end. The course should be named “Time Series Mathematical Primer” or something like that, IMO. INSTRUCTORS: Sadigov is an expert but he can’t teach. Add to this heavy accent and inability to speak clearly, and you have someone who would benefit from accent reduction training and adult learning training. The other lecturer, Thistleton, is easy to understand and conveys explanations rather than reading formulae out loud. Both are inferior to say, Galit Shmueli (https://bit.ly/2qM9eHL) whose free Time Series course online is clear and practical indeed, IMO. MATHEMATICS and THEORY: Although I had reasonable mathematical training in the past, I found parts of this course hard to follow and difficult to comprehend. I have been frustrated with the materials and having no ability to interact with the instructors or a teaching assistant. Most of the discussion topics / questions have no answers. Don’t expect any help from anyone, unless you formed your own study group with people you already know. BOTTOM LINE: While I do not regret taking this course, I feel I would have benefited more from a course whose material is more practical and whose instructors know how to teach.
Indresh T –
Course is really good to know the in depth understanding of the various models working around for the time series analysis.
Gasper U –
Very good! It would be very useful to do another tutorial for Python.
Abhishek S –
Awesome course. Instructors taught mathematical aspects with their implementation which made the learning fun and understandable. I hope to see advance course of this.
Joel A –
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.
Gilad G –
Great course! It gives a broad idea of how to deal with time series and some basic tools
Abhishek G –
Such an amazing course to learn the fundamentals theory and get the hands on experience with Time series data analysis. I really enjoyed learning through this course.
Ahtsham H –
a very good course
Dusan M –
Great experience!!!
NAFIS S F –
There should be more R codes and the explanation of the codes should be made easier. However, it is a good course on time series.