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Practical Time Series Analysis

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!

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Rating 4.4 based on 206 ratings
Length 7 weeks
Starts Jul 17 (41 weeks ago)
Cost $49
From The State University of New York via Coursera
Instructors Tural Sadigov, William Thistleton
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Math And Logic Probability And Statistics

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What people are saying

series analysis

The code meets its objective of teaching practical time series analysis.

I have found the mathematical formulations in time series analysis very useful.

A good source of learning time series analysis and forecasting!

It is a great course to learn Time Series Analysis.

I would recommend the instructors to add ARIMAX and multivariate time series analysis in the course as well.

Very nice to review those old concepts Course is really good to know the in depth understanding of the various models working around for the time series analysis.

I liked this course for two reasons mainly:It started from the basics of timeseries analysis, covering theory and secondly it took me gradually to r. Very good and structured lessons about fundamentals of time series modeling.

This is a great course for introduction to practical time series analysis.

Great content Grateful to the instructors for the engaging and fruitful learning I enjoyed in the course Practical Time Series Analysis!

great course even for newbies who're learning R. Good practical overview with lots of exercises 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/".

I am not a big fan of R (even after this course) but it seems its time series analysis libraries and datasets are comprehensive.

Overall, this is a good course for beginners in time series analysis.However, I wish they had go beyond the basics.

Easy to understand I found this course to have the right mixture of math and practical examples to illustrate the approaches for time series analysis.

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.

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introduction to time series

A complete introduction to Time Series, with a very good documentation.

It is a smooth introduction to time series analysis, very well explained and guided through multiple examples.

Very good introduction to Time Series with R. Emphases on concepts rather than on dry math, but also precise as needed.

This is a great course that provides strong introduction to time series analysis and forecasting.

Great introduction to time series with plenty of depth.

If you have some Math background, this course gives a good practical introduction to Time Series Analysis.

Course is good and intuitive and people not from non-mathematical/non-engineering backgroung may take more time in week 2 This is the first, and last, Coursera course i will do Exercises and Quizzes could be more complex The course is very good for an introduction to time series.

This was a good introduction to time series analysis.

This is a great introduction to time series analysis.

A great introduction to time series!

Very good and robust introduction to Time Series On other courses I received feedback on the forums in a prompt manner from the instructors, here none of my questions have been answered.

A very good introduction to time series analysis.

Nnice and smooth introduction to time Series that gives you a good basis to understand this topic.

Probably the best introduction to time series analysis I've ever seen.

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highly recommend

Highly recommended Practical Time Series Analysis help me understand more advanced statistical techniques.

It's very good for beginners.i highly recommended it.

Highly recommended.

I highly recommend it.

a great course for time series and forecasting, highly recommend :) Excellent course.

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recommend this course

I would definitely recommend this course.

highly recommend this course.

I would recommend this course.

I would look forward to see some more advance Time Series Courses like this.I would highly recommend this course to all the active learners willing to learn Time Series Analysis.

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.

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very helpful

this course was very helpful Thanks for the course!

All quizzes and in lecture questions were very helpful.

Great course for info about time series.Some parts (especially week 3 and 4) could be less mathematical.Should emphaise more on identifying the ranks of the models, for example - keep those questions in the quizes.Some quiz questions felt too easy :) very helpful!

It was a very helpful course.

Very helpful!

I think the course is very helpful and you learn how to perform time series analysis.

Very helpful Love this course.

This course is very helpful with making all concepts and applications clear.

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easy to follow

The lessons were easy to follow without much difficulty.

The class is easy to follow and the lecture notes are well prepared.

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.

Well presented material and relatively easy to follow.

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my opinion

In my opinion, a bit of practical applications of these models on Panel Data should be included.

In my opinion, it could have been better if more practical examples were given.

In my opinion there should be more practical exercises.

Thank you :) It was more theoretical than practical, in my opinion Great introductory course on time series.

In my opinion, it should include more practical cases focus on give to students a hands on feel of what happens by under all the math explained here.

As I understand there is some rule of thumbs but deeper explanations are missing to me (i hope, that they exists).Anyway in my opinion is the best course in Time Series Analysis, that I ever had.

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.

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practical examples

I found the course to be interesting, well organized and well taught, the teachers give intuitions and mathematical justifications to the theory and they provide extensive simulations and practical examples.Very recommended.

Excellent course, with practical examples and good explanation A very thorough course covering almost all the topics related to time series along with the math involved.

Well Structured with sufficient lectures, practical examples and quizzes.

Excellent introduction to the topic, and practical examples easy to apply to new data.

Great theories and practical examples.

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more advanced

(Or are you actually considering open another course with more advanced technique?

I hope the lecturers could provide more advanced classes.

would be even better if there is a optional lecture to cover some of the more advanced time series models.

I missed more advanced content, discussions between different forecasting techniques, multivariate forecasting...It is pretty basic.

It would be useful to have a more advanced subsequent course with the same features.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Adjunct Professor of Practical Theology $24k

Licensed Practical NurseRH BG $38k

Practical Examiner $45k

Lecturer in Practical Theology $46k

Licensed Practical or Vocational Nurse $48k

Licensed Practical Nurse Manager $52k

Licensed Practical Nurse Lead $63k

License Practical Nurse Manager $65k

Licensed Practical Nurse. $68k

Supervisor License Practical Nurse $70k

Licensed Practical Nurse (CLINICAL) $72k

Practical Process Improvement Project $99k

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Rating 4.4 based on 206 ratings
Length 7 weeks
Starts Jul 17 (41 weeks ago)
Cost $49
From The State University of New York via Coursera
Instructors Tural Sadigov, William Thistleton
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Math And Logic Probability And Statistics

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