This course is the second in a specialization for Machine Learning for Supply Chain Fundamentals. In this course, we explore all aspects of time series, especially for demand prediction. We'll start by gaining a foothold in the basic concepts surrounding time series, including stationarity, trend (drift), cyclicality, and seasonality. Then, we'll spend some time analyzing correlation methods in relation to time series (autocorrelation). In the 2nd half of the course, we'll focus on methods for demand prediction using time series, such as autoregressive models. Finally, we'll conclude with a project, predicting demand using ARIMA models in Python.
This course is part of the Machine Learning for Supply Chains Specialization
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About this Course
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Course 2 of 4 in the
Intermediate Level
Basic understanding of Python, Pandas, and Numpy.
Approx. 9 hours to complete
English
What you will learn
Building ARIMA models in Python to make demand predictions
Developing the framework for more advanced neural netowrks (such as LSTMs) by understanding autocorrelation and autoregressive models.
Skills you will gain
- Machine Learning
- Python Programming
- Autoregressive Integrated Moving Average (ARIMA)
- Time Series
- Demand Forecasting
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 4 in the
Intermediate Level
Basic understanding of Python, Pandas, and Numpy.
Approx. 9 hours to complete
English
Offered by
Syllabus - What you will learn from this course
2 hours to complete
A First Glance at Time Series
2 hours to complete
7 videos (Total 29 min), 3 readings, 2 quizzes
2 hours to complete
Independence and Autocorrelation
2 hours to complete
8 videos (Total 36 min), 2 readings, 2 quizzes
3 hours to complete
Regression and ARIMA Models
3 hours to complete
4 videos (Total 18 min), 1 reading, 2 quizzes
3 hours to complete
Final Project
3 hours to complete
Reviews
- 5 stars42.85%
- 4 stars4.76%
- 3 stars4.76%
- 2 stars23.80%
- 1 star23.80%
TOP REVIEWS FROM DEMAND FORECASTING USING TIME SERIES
by SFSep 12, 2022
Great course to gain fundemantals of Time Series Analyses for Demand Forecasting..
About the Machine Learning for Supply Chains Specialization

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