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Practical Time Series Analysis

4.5

170 reviews

Created by: Tural Sadigov

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Overall Score : 90 / 100

Course Description

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!

Time: 25h

Instructor Details

Tural Sadigov

4.5 Rating
170 Reviews

CoursesPractical Time Series Analysis

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4.5

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By Manjeet K on 16-Nov-19

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.

By Neel D on 15-Nov-19

Too much detail and outdated course

By Paulo H S V on 10-Nov-19

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

By David R on 9-Nov-19

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.

By Herman d V on 6-Nov-19

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!

By Lucia on 21-Oct-19

Pretty good! I enjoy the course very much.

By Lance D on 20-Oct-19

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 chundarathil a on 19-Oct-19