Time Series Forecasting Using Python Course Overview

Discover the powerful techniques of Time Series Forecasting using Python in just 3 days with Koenig Solutions. This comprehensive 24-hour course will help you understand the differences between time series data and cross-sectional data, and equip you to transform datasets into time series for analysis. You’ll start coding in Python, conduct accurate time-series analysis, and interpret results effectively. Learn to normalize data, handle special series like White Noise and Random Walks, and manage autocorrelation and unexpected shocks. Practical modules will ensure you grasp model selection, stationarity tests, integration use, and volatility measurement. By the end, you'll be forecasting future trends based on past data patterns, ready to apply these skills in real-world scenarios.