PHAROS AI Factory announced the 4th Course of its Training Series, ML Track:  “Introduction to Time Series Forecasting“, held online via Zoom, on March 9th, 2026. 

Presentation language: Greek

Audience: This course wass intended for postgraduate students in computer science and economics, researchers, employees of small and medium-sized enterprises (SMEs), data scientists, and machine learning engineers, as well as anyone interested in applying time series forecasting techniques to real-world, data-driven problems.

Location: Online via Zoom

Description: 

This course provided a complete, hands-on introduction to time series forecasting, starting from the fundamentals of what time series data is and why its analysis is essential. Participants learned why forecasting plays a critical role in decision making, how data analysis and preprocessing are integrated into the forecasting pipeline, and how insights are extracted from temporal data. The session covered classical statistical models for time series forecasting. Through practical, end-to-end examples, attendees implemented forecasting models, gained a solid understanding of the underlying theory, and applied these techniques to real-world scenarios.

Learning Outcomes:

Upon successful completion of this course, participants were able to systematically handle time series data, applying appropriate analytical tools and methodologies to address real-world forecasting challenges. They developed a structured analytical mindset, understanding the end-to-end forecasting pipeline—from problem definition and data preprocessing to model selection, evaluation, and interpretation of results—while being able to identify patterns, trends, and seasonality within temporal data.

The course’s presentation can be found here.

The course’s recordings can be found here.