- Python Programming
- Predictive Analytics
- Plot (Graphics)
- Time Series Analysis and Forecasting
- Demand Planning
- Applied Machine Learning
- Machine Learning
- Forecasting
- Exploratory Data Analysis
- Matplotlib
- Customer Demand Planning
- Correlation Analysis
Demand Forecasting Using Time Series
Completed by Rajesh Telikicherla
February 22, 2024
9 hours (approximately)
Rajesh Telikicherla's account is verified. Coursera certifies their successful completion of Demand Forecasting Using Time Series
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
