The Pharos Training Series

• Nikos Bakas (GRNET)

Introduction to Timeseries Forecasting

• Nikos Bakas (GRNET)

Forecasting & AI: Live Q&As with Professor Spyros Makridakis

• Spyros Makridakis (University of Nicosia)

Introduction & Objectives Overview of time series forecasting, webinar goals, structure, and expected outcomes.

Theory Session I: Fundamentals of Time Series Analysis Definition of time series data, key components, the importance of forecasting, and the role of data analysis.

Hands-On Session I: Data Analysis & Statistical Models Practical implementation of data preprocessing, exploratory analysis, and classical statistical forecasting models.

Theory Session II: Machine Learning & Deep Learning for Time Series Concepts, architectures, and methodologies for machine learning and deep learning–based forecasting.

Hands-On Session II: ML & DL Forecasting Models End-to-end development, training, and evaluation of machine learning and deep learning models.

Core Use Case: End-to-End Forecasting Application A complete real-world case study integrating all theoretical and practical elements covered in the webinar.

Live Q&A Session Open discussion and clarification of concepts, methods, and implementation details.

Wrap-Up, Key Takeaways & Resources Summary of key insights, lessons learned, and resources for further study and application.