Machine Learning for Time Series using Python -Online recordings
and live Q&A 

This intensive five-day online course provides a practical introduction
to machine learning techniques for modelling, analysing, and
forecasting time-series data using Python. Designed for researchers,
analysts, and data scientists who work with temporal datasets, the
course focuses on hands-on workflows that can be applied directly
to real-world problems.

Participants will learn how to prepare and visualise time-series
data, implement machine learning models for forecasting and
classification, evaluate model performance, and interpret results
in a statistically sound way. The training combines structured
teaching with guided exercises, giving attendees experience with
modern Python tools and methods commonly used in time-series analysis.

All sessions are delivered live online and recorded for later review,
with opportunities for questions and discussion during dedicated
Q&A sessions.

Course details
Dates: 11-15 May 2026
Format: Online recordings and live Q&A
Fee: �450
This course is suitable for professionals and postgraduate researchers
who have basic familiarity with Python or data analysis and want
to develop practical machine learning skills for time-dependent
data.

Register here:
https://prstats.org/course/machine-learning-for-time-series-mltp01/

Oliver Hooker PhD.

PR stats

Oliver Hooker <oliverhooker@prstatistics.com>

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