Zurück zu Practical Time Series Analysis

4.6

Sterne

1,115 Bewertungen

•

313 Bewertungen

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!...

JM

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.

RT

Jul 17, 2020

Easily one of the best time-series courses online. Although it says "practical", there is plenty of good theory to back up the practice and at the same time not overwhelming or distracting.

Filtern nach:

von Luca B

•Feb 21, 2020

Very well explained! Both instructors are very competent and are complementary in their way of explaining and simplifying complex concepts. It took me five days to complete this course and I really had fun going through the theoretical details behind widely used techniques such as ARIMA and SARIMA, as well as understanding the applications of the techniques. The course is well structured and easy to follow. There is just enough theory to understand the basic concepts, applications being the main focus of this course. Congratulations to the instructors for this great course and thanks a lot for putting all the efforts to make it accessible to people that have not worked with time series before!

von Solomon W

•Mar 09, 2018

This is a great course that provides strong introduction to time series analysis and forecasting. I have benefited a lot from it as I took it to advance my career in data science. I have found the mathematical formulations in time series analysis very useful. I have also found the forecasting sections equally useful. All quizzes and in lecture questions were very helpful. The R coding practices are certainly helpful in learning the corresponding R libraries; they also provide template code that is useful for writing custom code for analysis.Many thanks to the instructors!

von Eddie C

•Aug 08, 2020

I enjoyed and highly recommend the course! Both instructors explained the main concepts of time series analysis clearly. The practical aspects involved using R on various data sets.

The multiple worked examples were very useful in clarifying the concepts. The exercises and quizzes were generally direct applications of the examples. and thus very useful in helping to reinforcing the concepts learned. Clear explanations were even given for why certain choices were correct/wrong, which is not often the case for other coursera courses.

I hope for a more advanced course soon!

von Michael D

•Jun 14, 2018

I enjoyed the course, especially the theoretical part.Also I would wish there would more course, on Time Series Analysis at Coursera. Currently there is only one such course.In this course, I wish there would be more reference to the literature. Some points as determination of AR & MA order by looking at ACF & PACF plots is not clear enough to me. 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.

von Jeeva V

•Jul 04, 2018

The first three weeks it is hard to understand as the course content was not properly organized. some chapters and quizzes are jumbled without order. It has a lot of theory as well. But then after understanding the basics, the theoretical concepts, it is easy to follow. It gave very confident and in fact already started applying in my real world time series problems to model and forecast for future time period. Great course and would recommend to friends who are serious to learn about practical time series analysis.

von HEF

•Apr 28, 2019

The course structure is well organized from basic statistics to more advanced materials. I used to hate reading but in this course I found the reading materials quite pleasant and interesting. Only light coding involved so I guess people without coding experience would find it friendly as well. Both theoretical and applied aspects were discussed in details, and I got to know many valuable sources of finding interesting time series datasets. In summary, a really great course one must take a try!

von 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.

von Yakup T K

•May 18, 2020

A good lesson to cover what under the hood of additive models like ARIMA and Holt-Winters Exponential Smoothing etc. It gives you the idea of what to approach time series, mathematical internals and some basic proofs. It helps you a lot to decompose a time serie in terms of seasonality, trend, autoregressive and moving average process components after making some statistical tests. It helped me to use it for my job to forecast some time series in a more accurate way.

von Anup K Y

•Sep 05, 2020

Very well structured course and comprehensive study material available with the modules. Despite these, I found some gaps in practical support, but I did my own because I am familiar with the R software environment, overall it was a great experience. I request the teachers and team of this course to kindly make its second version module for advanced time series models (eg, ARCH, GARCH, ARDL etc.). I would like to join that too. Thanks!

von 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

von Chunhui G

•Jul 15, 2019

The course is very good for an introduction to time series. Few drawbacks are listed.

1. The theory behind double and triple exponential forecast are not given in the materials.

2. Some datasets are not available anymore in the Datamarket website anymore, needed to be fixed.

3. The forecast module in week 6 is kind of wired. Need more lecture to talk about what's the difference between smooth forecast and SARIMA model prediction.

von Manish k

•Aug 30, 2018

The course structure is really nice and focused on hand's on application of Time series analysis. I was able to understand the maths also quite well, thanks to the Tutor for such a simplified explanation. 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.

von Pratik C

•Jun 10, 2018

Excellent course. The whole topic is broken into bits and pieces and in a well structured form. Makes it easier to understand each concept. Apart from quizzes, few assignment problems where from the given data-set you need to come up with which technique to be used whether SARIMA or Exponential forecasting and then final forecast numbers. This will make it a complete course.

von Anthony A Q D

•Sep 14, 2018

It's really good. I'm a master of applied statistic student and haven't taken time series. It helped me a lot, the math can be decently challenging but was rewarding when I did it. The vocabulary are very obtuse though. Trend, stationarity, etc.. is lost in the details. Process order and lag relationship was somewhat lost in the detail. Overall I learned a lot thank you!

von ZHOU G

•May 12, 2018

Thanks for the course! I found it very interesting and useful.

I believe the course could be improved by having a proper ending or conclusion, reviewing everything we have learned and introduce some some viable path through which we can further advance the analysis skill. (Or are you actually considering open another course with more advanced technique?

Thanks again!

von 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.

von Zhexuan Z

•Aug 14, 2019

Really good course to get to the fundamental concepts of AR, MA, ARIMA, SARIMA process, and basic concept like stationary. A few more areas that I wish the class could cover, including 1) stationary tests like ADF, KPSS, etc 2) regression against time series variables and how to treat/transform these variables before running regression model

von Sanathkumar P

•Oct 03, 2018

I found this course to have the right mixture of math and practical examples to illustrate the approaches for time series analysis. Even if some parts of got too mathy, I was still able to understand it. Considering that its been a while since I have dealt with math, it should be encouraging for others having similar reservations.

von Andrea P

•Jan 24, 2020

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.

von Girija V

•May 03, 2020

The course covers almost everything related to time series in detail. The mathematics is not too tough to understand but the jist of the course is how to apply time series models to real world datasets. Hats Off to the professors for covering each and every detail thoroughly. Highly recommended !!

von Abinaya A R

•Sep 23, 2018

I had an wonderful experience learning this course. Descriptions and teaching methodology was quite comfortable with me. The reading materials and the lectures together provided an overall understanding of the contents. Happy to have found and completed this course.

von Logan S

•Oct 23, 2018

Great course. Once you get your mind around the math with the real-world examples the applications and understanding become quite obvious. Would recommend just presenting the checklist at the outset so learners know that they're building into a framework.

von Ciprian C C

•Mar 31, 2018

I like this course and the instructors are great. Mostly, they showed care for the students by making the exercises well chosen and accessible, which greatly increases the confidence of the student. The pace of the material is balanced too. I enjoyed it!

von MEKALA S N

•May 25, 2020

very good course for a person who doesn't have an experience in time series and R.Clearly explained every model with mathematical modelling and proof.Very satisified with the course now, i am confident that i can model any time series data.Thanks a lot

von 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.

- Sinn und Zweck im Leben finden
- Medizinische Forschung verstehen
- Japanisch für Anfänger
- Einführung in Cloud Computing
- Grundlagen der Achtsamkeit
- Grundlagen des Finanzwesens
- Maschinelles Lernen
- Maschinelles Lernen mittels Sas Viya
- Die Wissenschaft des Wohlbefindens
- Contact-Tracing im Kontext von COVID-19
- KI für alle
- Finanzmärkte
- Einführung in die Psychologie
- Erste Schritte mit AWS
- Internationales Marketing
- C++
- Predictive Analytics und Data-Mining
- UCSD: Learning How to Learn
- Michigan: Programming for Everybody
- JHU: R-Programmierung
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- KI für Medizin
- Guter Umgang mit Worten: Redaktionelles Schreiben
- Modellbildung von Infektionskrankheiten
- Die Aussprache des US-amerikanischen Englisch
- Software-Testautomatisierung
- Deep Learning
- Python für alle
- Data Science
- Geschäftsgründungen
- Excel-Kenntnisse für Beruf
- Data Science mit Python
- Finance for Everyone
- Kommunikationsfähigkeiten für Ingenieure
- Verkaufstraining
- Career Brand Management
- Wharton: Unternehmensanalytik
- Penn: Positive Psychology
- Washington: Maschinelles Lernen
- CalArts: Grafikdesign

- Zertifikate über berufliche Qualifikation
- MasterTrack-Zertifizierungen
- Google IT-Support
- IBM Datenverarbeitung
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI: Angewandtes Projektmanagement
- Zertifizierung in Instructional Design
- Zertifizierung in Bauwesen und -management
- Zertifizierung in Big Data
- Zertifizierung Maschinelles Lernen für Analytics
- Zertifizierung in Innovation Management & Entrepreneurship
- Zertifizierung in Nachhaltigkeit und Entwicklung
- Zertifizierung in Soziale Arbeit
- Zertifizierung KI und maschinelles Lernen
- Zertifizierung in Räumliche Datenanalyse und Visualisierung

- Abschlüsse in Informatik
- Business-Abschlüsse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Data Science
- Bachelorabschlüsse
- Bachelor of Computer Science
- MS Elektrotechnik
- Bachelor Completion Degree
- MS Management
- MS Informatik
- MPH
- Master-Abschluss in Buchhaltung
- MCIT
- MBA online
- Master of Applied Data Science
- Global MBA
- Master in Innovation & Entrepreneurship
- MCS Data Science
- Master in Informatik
- Master-Abschluss in Public Health