Voltar para Practical Time Series Analysis

4.6

700 classificações

•

185 avaliações

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.

Aug 03, 2019

A nice course which is practical as the name said, it balanced the portion of theories and practices. I used to not familiar with this topic, but now I consider myself much more familiar.

Filtrar por:

por Laurentiu N

•Aug 16, 2018

Terrible explanations... they do not make any sense....

Basically the instructors are reading mathematical expressions. No intuition, no significance, you are taught mechanically, sorry to say it

I wont buy anything from this provider ever.

por Benjamin O A

•Jul 26, 2018

This is one of the best courses I've taken so far on Coursera. The exercises and delivery are so practical. I had taken a college course in Time Series Analysis, but didn't pretty much understand the concepts. This course has given me far better theoretical and practical understanding of TMS. A big thanks to the professors.

por xun y

•Dec 16, 2018

Great introductory course on time series. Focus on ARIMA model most of the time while the last lecture capture a little bit of exponential smoothing. Would be great if there if summary lecture regarding to when to use which modeling technique. would be even better if there is a optional lecture to cover some of the more advanced time series models.

por Lingbing F

•Jul 05, 2019

a good course on univariate time series modelling by ARMA type models, with additional details on Yule Walker equations, seasonal models, and forecasting.

por Janki M

•Mar 21, 2019

This was a very good and detailed course. 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.

por Roberto G A

•May 23, 2019

Excellent

por Martin H A

•Mar 30, 2018

I found one of the instructors (Thistleton) much clearer and didactic than the other. I would have liked a deeper formal insight into the models that were discussed: limitations, assumptions, what kind of physical models they can represent? what to do with systems that don't behave "nicely"?, etc.

por Kanchan K

•Nov 17, 2019

It is a good course if you want to learn about the basic concepts of time series

por Heberto S

•Apr 01, 2019

There was not a good intuitive and more visual explanations of the principles behind the techniques.

Given the proposed 'practical' nature of the course, it would be better to explain any concept by using concrete every-day examples than preceding them with a elaborated mathematical reasoning of the equations used.

por Juan M G H

•Sep 26, 2018

On other courses I received feedback on the forums in a prompt manner from the instructors, here none of my questions have been answered.

por Neel D

•Nov 15, 2019

Too much detail and outdated course

por VB

•Jul 26, 2019

Nothing practical, real example are used to enhance theoretical stuff.

Not a single example of practical use.

Too many mistakes in course - quizes are based on following week materials, materials are titeled with mistakes, there are mistakes in narratives in addition to the mistakes in what is talked.

One of the lecturer is talking like he has to read slides as quickly as possible, because he is to buisy with other stuff.

Too much math. you have to know algebra really well to understand what he is talking about.

you should learn some R by yourself, because it is not

explained how to do a lot of things. i think R should be in cluded in course title, to make people know in advance...

my score is 1.4(9) stars....

por Supratim C

•Sep 25, 2019

Very monotonous lectures. They feel like a recitation of formulae.

por Mohammed M A

•Dec 31, 2018

Grateful to the instructors for the engaging and fruitful learning I enjoyed in the course Practical Time Series Analysis! Thank you :)

por Sai R

•Jan 27, 2019

First I started out reading Intro to Time Series and Forecasting, the book suggested by everyone. But, I could not understand the math because it was too tough. I did not lose hope. I completed this course because sometimes you need to get an overview of what needs to be done and then if you dive into the math of it, it will be easy. Much recommended course for the beginning of time series and forecasting techniques. 5 stars! Thank you

por Anas M

•Jan 27, 2019

A Well structured and well taught course thank you !

por Matthew C Z

•Jan 28, 2019

Great course, I highly recommend!

por Ramachandra R K

•Nov 08, 2018

Decent course with a right balance between math, coding and high level explanation. AR, MA and ARMA (ARIMA) models are very well explained. I am not a big fan of R (even after this course) but it seems its time series analysis libraries and datasets are comprehensive. The best part of the course is the in-course coding examples and tasks. They really help you get hands-on into analysing various time series objects. A little more emphasis should have been made on forecasting.

por Vidhyalakshmi K

•Nov 24, 2018

The course is very insightful substantively covering both theory and practical in a balanced manner. I liked it very much.

por Ahmad L

•Nov 24, 2018

great course even for newbies who're learning R.

por Robert S

•Nov 11, 2018

The instructors provided detailed background for the theoretically inclined while gradually developing practical implementations in R using many real time series. Having finished the course I have a firm grasp of the process of analyzing time series and forecasting from them, as well as greater general facility in R. Overall an excellent and useful course.

por Chinmay J D

•Jan 05, 2019

Excellent coursework !! Very less amount of theory is required and hence a very useful for beginners.

por Krzysztof S

•Jan 11, 2019

The topic is very difficult, but lectures explain everything in very clear way.

por Jie F

•Feb 13, 2019

very good course for time series study

por Dongliang Z

•Feb 15, 2019

Terrific! Thanks the teachers! Both of You are very good. You make the complexity easy to learn.

Nice theory, Nice example, Nice code, Nice pdf files.

I will definitely review this course again and again whenever I need to use time series to forecast.

O Coursera proporciona acesso universal à melhor educação do mundo fazendo parcerias com as melhores universidades e organizações para oferecer cursos on-line.