> Markdown version of [/events/conference-india-2026/sessions/2002-modern-forecasting](https://www.wearedevelopers.com/events/conference-india-2026/sessions/2002-modern-forecasting). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

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# Modern forecasting with sktime - foundation models, agents, and benchmarks


- **Event:** Conference India 2026

## Description

Forecasting is evolving rapidly, with deep learning, foundation models, and agentic AI opening up new possibilities while making it increasingly difficult to compare methods fairly and identify the right approach for a given application.

This hands-on workshop provides a practical introduction to modern forecasting with sktime, demonstrating how a unified framework enables users to experiment with a broad ecosystem of forecasting methods while maintaining reproducibility and transparency.

Rather than focusing on individual algorithms in depth, the workshop follows a use-case-driven overview of the forecasting workflow.

Participants will learn how to work with classical statistical models, modern deep learning architectures, and emerging foundation models through a consistent interface, while also exploring the latest agentic capabilities for automating forecasting tasks.

The emphasis is on understanding how these components fit together in real-world forecasting pipelines and how to move efficiently from experimentation to evaluation.

A central theme of the workshop is trustworthy benchmarking. Participants will learn how to set up neutral, reproducible benchmark experiments, compare forecasting methods - including foundation models and agents - under consistent evaluation protocols, and build their own benchmarking studies that can scale from local machines to larger compute environments.

By the end of the session, attendees will have the practical knowledge and tooling needed to evaluate forecasting approaches on their own data, reproduce published results, and confidently select models based on evidence rather than hype.

The workshop is intended for data scientists, machine learning practitioners, and researchers with basic Python knowledge who want a practical overview of the modern forecasting landscape and hands-on experience with the latest capabilities of the sktime ecosystem.

## Speakers

### [Aryan Saini](https://www.wearedevelopers.com/@aryan-saini)

Core Developer at sktime
### [Franz Kiraly](https://www.wearedevelopers.com/@franz-kiraly)

Director, German Center for Open Source AI
### [Jigyasu ㅤ](https://www.wearedevelopers.com/@jigyasu)

Core developer, sktime


## Related talks at this congress

- [Agentic Forecasting with sktime: Towards Autonomous Time Series Analysis](https://www.wearedevelopers.com/events/conference-india-2026/sessions/2001-agentic-forecasting) — Franz Kiraly
- [Build a Zero-Cost AI Agent in Your Browser](https://www.wearedevelopers.com/events/conference-india-2026/sessions/1980-build-a-zero-cost-ai) — Aishwarya Mathuria, Nishant Thakur
- [Architecting Trusted AI: Coupling Multi-Agent Systems with dbt Semantic Store for Zero-Hallucination](https://www.wearedevelopers.com/events/conference-india-2026/sessions/1976-architecting-trusted) — Pushkar Mishra
- [Beyond File Dumps: Context Engineering for Coding Agents](https://www.wearedevelopers.com/events/conference-india-2026/sessions/1979-beyond-file-dumps) — Animesh Dutta

## Watch remotely

Can’t make it to Bengaluru? Watch this session live with Pro. You also get:

- All full videos, bookmarks, and playlists
- World Congress livestreams

[See pricing](https://www.wearedevelopers.com/pricing)

## Links

- [Get tickets](https://www.wearedevelopers.com/conference-india/tickets)