Enroll Course: https://www.coursera.org/learn/demand-prediction-using-time-series
If you’re interested in elevating your skills in demand forecasting and gaining practical insights into time series analysis, the Coursera course “Demand Forecasting Using Time Series” is an excellent choice. This course is part of the Machine Learning for Supply Chain Fundamentals specialization and offers a comprehensive overview of how time series data can be leveraged to predict demand accurately.
The course begins with foundational concepts such as stationarity, trend, cyclicality, and seasonality, essential for understanding the behavior of time series data. You’ll learn to visualize and analyze time series in Python, exploring the differences between seasonality and cyclicality. The modules delve into autocorrelation and how it relates to independence, enriching your understanding of data relationships.
A significant highlight is the practical focus on regression techniques and ARIMA models. The course guides you through implementing lagged regression and ARIMA, setting the stage for more advanced models like LSTMs. The hands-on final project involves creating demand predictions using ARIMA, solidifying your learning.
Overall, this course is highly recommended for data enthusiasts, supply chain professionals, and machine learning practitioners seeking to deepen their understanding of demand forecasting through time series. The blend of theoretical concepts and practical coding exercises makes it a valuable addition to any data science toolkit.
Enroll Course: https://www.coursera.org/learn/demand-prediction-using-time-series