Horizon University

This module provides a comprehensive introduction to time series forecasting, combining statistical foundations with modern deep learning techniques. Students will explore methods ranging from classical approaches such as ARIMA, SARIMA, and Exponential Smoothing to advanced neural network architectures like RNNs, LSTMs, and Temporal Convolutional Networks. The course emphasizes both theoretical understanding and practical implementation, enabling students to preprocess data, identify patterns of trend and seasonality, build predictive models, and evaluate their performance using standard forecasting metrics. Through interactive labs and case studies, learners will gain the skills needed to apply forecasting techniques to real-world domains such as finance, healthcare, and retail.

This course is a Template, please add your description and change the course photo.

This course is a Template, please add your description and change the course photo.

This course is a Template, please add your description and change the course photo.