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, 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 avis)
Expérience recommandée
Ce que vous apprendrez
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.
Compétences que vous acquerrez
- Catégorie : Time Series Data Analysis
- Catégorie : Data Interpretation
- Catégorie : Forecasting Techniques
- Catégorie : ETS Modeling
- Catégorie : ARIMA Modeling
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Il y a un module dans ce cours
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.
Inclus
16 vidéos4 lectures1 devoir2 sujets de discussion
Instructeur
Offert par
Recommandé si vous êtes intéressé(e) par Business Essentials
Coursera Project Network
Coursera Instructor Network
University of Illinois Urbana-Champaign
University of Colorado System
Pour quelles raisons les étudiants sur Coursera nous choisissent-ils pour leur carrière ?
Avis des étudiants
20 avis
- 5 stars
40 %
- 4 stars
15 %
- 3 stars
15 %
- 2 stars
15 %
- 1 star
15 %
Affichage de 3 sur 20
Révisé le 16 oct. 2024
Best explanation of the key concepts in short time. Well done.
Révisé le 12 juin 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
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