A wide variety of data science tasks, ranging from financial stock market trading to inventory management to sales planning, requires understanding time trends and issuing time forecasts. These types of tasks leverage repeatedly measured data records across a span of time, called time series. In this course, we will introduce techniques for time series analysis and forecasting and their applications in business settings, including thorough discussion of canonical ARIMA models and brief introduction to deep-learning-based models such as recurrent neural networks and transformers.
prereq: MSBA 6121, MSBA 6131, or instructor consent