sktime

Cohort 1

Apr-May 2025

June 2025

September 2025

Nov-Dec 2025

A gentle introduction for newcomers, and a deep-dive into advanced topics such as hierarchical forecasting, foundation models

senior data scientist retail forecasting

Robert Kübler, Ph.D.

Senior Staff Data Scientist at ALDI Süd, forecasting for retail

creator sktime forecasting toolbox

Franz Király, Ph.D.

Director, German Center of Open Source AI, and founder of sktime

content creator, founder MLboost

Mahdi Torabi Rad, Ph.D.

Content creator tech & AI, founder and data science consultant and MLBoost

forecasting for e-commerce and retail

Felipe Angelim, MSc

sktime core developer, forecasting for e-commerce, finance, and retail

Python Forecasting Masterclass: From Foundations to State-of-the-Art

Data Scientist

developer

- From Python forecasting basics to foundation models in four weeks- Use-case driven with examples, methodologically solid- Learn to code in sktime, the leading forecasting framework- Onboard to the sktime community of practice - stay up-to-date forever!- No biased product placement or hidden advertisement of paid services- Become an expert and support open source - 50% towards sktime maintenance and development

Master forecasting in Python and join a growing community of practice

Diagnose data and learning task accurately

Model composition, pipelines, AutoML

Probabilistic forecasting

Hierarchical forecasting, global forecasting

Cutting edge model types and techniques

Using sktime - the leading forecasting package

Ideal for beginners with a grasp of machine learning. Learn time series forecasting in Python, from the ground up.

Expand and complete your toolkit, stay up-to-date. Learn about the newest techniques and cutting-edge methods.

For professional practitioners. Learn from basics to advanced techniques, tailored for real-world impact, with use-case examples.

AI for forecasting: foundations models, hype & best practice

Franz Kiraly

Gentle introduction to foundation and pre-trained models. Zero-shot, few-shot, fine-tuning; open vs gated, etc

forecasting foundation models - what they are, what they do

special considerations and "FMops" for forecasting - FM handling (best) practice, key difficulties & solutions

best practice - handling software, weights, deps, evaluation

lock-in tactics, influencer propaganda, gated/closed models, licenses, full-value open alternatives

... and what the vendors don't want you to know about

Learn directly from sktime

sktime

Courses

Python Forecasting Masterclass: From Foundations to State-of-the-Art

Lightning Lessons

AI for forecasting: foundations models, hype & best practice