Learn main advanced forecasting models concepts from proficient to expert level through a practical course with Excel.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Identify Box-Jenkins autoregressive integrated moving average model integration order through level and differentiated time series first order trend stationary deterministic test and Phillips-Perron unit root test.
Recognize autoregressive integrated moving average model autoregressive and moving average orders through autocorrelation and partial autocorrelation functions.
Estimate autoregressive integrated moving average models such as random walk with drift and differentiated first order autoregressive.
Identify seasonal autoregressive integrated moving average model seasonal integration order through level and seasonally differentiated time series first order seasonal stationary deterministic test.
Estimate seasonal autoregressive integrated moving average models such as seasonal random walk with drift and seasonally differentiated first order autoregressive.
This comprehensive Advanced Forecasting Models with Excel curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
What you need before starting this Advanced Forecasting Models with Excel course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Diego Fernandez
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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