Time Series Analysis

Intermediate

6-week course | 4 hours/week

Course Introduction

This course provides comprehensive training in time series analysis techniques, covering both traditional statistical methods and modern machine learning approaches for temporal data.

Course Content

  • Week 1: Time Series Fundamentals and Visualization
  • Week 2: Stationarity and Differencing
  • Week 3: ARIMA Models
  • Week 4: Seasonal Decomposition
  • Week 5: Forecasting Techniques
  • Week 6: Advanced Topics (GARCH, VAR, LSTMs)

Assignments

Assignment 1: Time Series Exploration

Analyze and visualize time series patterns in economic data.

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Assignment 2: ARIMA Modeling

Build and validate ARIMA models for forecasting.

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Assignment 3: Forecasting Challenge

Compare different forecasting methods on real-world data.

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Case Studies

Stock Market Analysis

Model and forecast stock price movements using time series techniques.

Energy Demand Forecasting

Predict electricity demand patterns for utility planning.

Datasets

  • "Time Series Analysis" by James D. Hamilton
  • "Forecasting: Principles and Practice" by Rob J Hyndman
  • "Analysis of Financial Time Series" by Ruey S. Tsay