Data Analytics and Panel Techniques

Overview

This course provides a comprehensive introduction to machine learning and deep learning concepts, techniques, and applications. Participants gain the skills to analyze data, build predictive models, and develop deep learning architectures using contemporary tools and frameworks. The program emphasizes hands-on experience and critical thinking, enabling learners to solve real-world problems across diverse domains using AI-powered approaches.

Key Highlights

• Advanced panel data techniques, focusing on Common Correlated Effects (CCE) methods
• Extensions to dynamic specifications for robust macroeconomic analysis
• Addressing cross-sectional dependence and unobserved global factors in heterogeneous economies
• Integration of latent common factors for enhanced modeling flexibility and robustness
• Practical application of methods to real-world macroeconomic datasets

Skills Developed

• Machine learning and deep learning model development
• Data analytics and predictive modeling
• Advanced econometric techniques for macroeconomic research
• Application of AI methods to complex, interconnected economic systems