enthaltenIn today's data-driven world, the ability to accurately forecast and predict future trends is crucial for businesses to stay ahead of the competition. Time series analysis is a powerful tool that allows organizations to unravel patterns and make informed decisions. This course, Time Series Mastery: Unravelling Patterns with ETS, ARIMA, and Advanced Forecasting Techniques, provides a comprehensive introduction to time series analysis and forecasting. You will learn about the most widely used techniques, including Error-Trend-Seasonality (ETS), Autoregressive Integrated Moving Average (ARIMA), and advanced forecasting methods. By the end of this course, you will have the skills and knowledge to apply these techniques to real-world data and make accurate predictions.
(20 Bewertungen)
Empfohlene Erfahrung
Was Sie lernen werden
Apply the most widely used techniques, including Exponential Smoothing (ETS) and Autoregressive Integrated Moving Average (ARIMA).
Analyze real-world data to identify patterns and make accurate predictions.
Create advanced forecasting models using Python.
Kompetenzen, die Sie erwerben
- Kategorie: Time Series Data Analysis
- Kategorie: Data Interpretation
- Kategorie: Forecasting Techniques
- Kategorie: ETS Modeling
- Kategorie: ARIMA Modeling
Wichtige Details
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In diesem Kurs gibt es 1 Modul
In today's data-driven world, the ability to accurately forecast and predict future trends is crucial for businesses to stay ahead of the competition. Time series analysis is a powerful tool that allows organizations to unravel patterns and make informed decisions. This course provides a comprehensive introduction to time series analysis and forecasting. You will learn about the most widely used techniques, including Error-Trend-Seasonality (ETS), Autoregressive Integrated Moving Average (ARIMA), and advanced forecasting methods.
Das ist alles enthalten
16 Videos4 Lektüren1 Aufgabe2 Diskussionsthemen
Dozent
Empfohlen, wenn Sie sich für Business Essentials interessieren
University of Illinois Urbana-Champaign
University of Colorado Boulder
Fundação Instituto de Administração
University of Pennsylvania
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Bewertungen von Lernenden
20 Bewertungen
- 5 stars
40 %
- 4 stars
15 %
- 3 stars
15 %
- 2 stars
15 %
- 1 star
15 %
Zeigt 3 von 20 an
Geprüft am 12. Juni 2024
I think it was too basic, it lacks more a deeper dive into theoretical aspects and importance about the different scores that the summary of the model provides. However it's a good introduction
Geprüft am 16. Okt. 2024
Best explanation of the key concepts in short time. Well done.
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