Time Series Analysis in Python: Theory, Modeling: AR to SARIMAX, Vector Models, GARCH, Auto ARIMA, Forecasting
InstructorAkhil VydyulaComidoc has tracked 13 coupons for this course since 2025, last checked 2d ago. On average, a new coupon appears roughly every 21 days.
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The curriculum spans from Python data structures and business statistics to advanced forecasting models like SARIMA and LSTM.
Instruction concludes with a capstone project involving the forecasting of UK road accident rates using multiple modeling approaches.
Editorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This notebook cell illustrates univariate time series analysis by displaying a dataset of shampoo sales alongside a line chart that reveals the underlying trend.
This notebook page illustrates key time series characteristics using three distinct graphs that visualize concepts like constant mean, changing standard deviation, and periodic seasonality.
The notebook interface displays a hand-drawn time series graph on grid paper, flanked by various pens and markers to illustrate the visual analysis concepts.
Learner feedback suggests that core concepts such as stationarity, random walks, and ACF/PACF may lack sufficient detail, necessitating external research.
The curriculum aligns well with the stated goals of aspiring data scientists and those interested in finance through its Python and statistical focus.
