Whether it’s quarterly sales data, stock prices, automated inventory trading, or even weather data, time series data is all around us. And working with time series data is a crucial skillset for data practitioners. Ideal for those aiming to refine inventory forecasts, predict market trends, or understand user behaviour, this course offers a direct route to mastering sophisticated time series analysis techniques with Python.

Participants begin the course by learning the foundations, including preprocessing steps for time series data in Python and Pandas, and thinking about time series data as consisting of a trend component, a seasonal component, and observational noise. From there, they explore various core modelling and forecasting techniques they can leverage including ARMA, SARIMAX, Exponential smoothing, and the approach taken in the Python library, Prophet.

Through practical application, your team will master the intricacies of financial markets, supply chain dynamics, consumer behaviour, and product usage trends. This hands-on experience not only enhances strategic decision-making but also significantly contributes to your organisation's overall success.