A Practical Approach to Timeseries Forecasting Using Python
Completed by Daniel Cooke
March 23, 2026
15 hours (approximately)
Daniel Cooke's account is verified. Coursera certifies their successful completion of A Practical Approach to Timeseries Forecasting Using Python
What you will learn
Visualize and manipulate time series data using Python and key libraries
Build and tune ARIMA and SARIMA models for effective forecasting
Implement LSTM, BiLSTM, and GRU models for deep learning-based predictions
Design end-to-end forecasting pipelines for real-world datasets
Skills you will gain
- Category: Predictive Analytics
- Category: Machine Learning Methods
- Category: Data Processing
- Category: Data Visualization Software
- Category: Recurrent Neural Networks (RNNs)
- Category: Feature Engineering
- Category: Data Preprocessing
- Category: Forecasting
- Category: Statistical Modeling
- Category: Model Optimization
- Category: Model Evaluation
