All training programmes — Jura Contact us

AI training in the canton of Jura

In the canton of Jura, AI training serves industrial and craft SMEs, from Delémont to the Franches-Montagnes: working on fictional supplier enquiries and distinguishing administrative assistance from approval of an industrial commitment.

Start with real work and a local context

The situation described here is a learning example, not an account of completed work. Before the session, SHR selects a representative task with you — a note, an instruction, a summary or a reply — and sets the criteria by which the result will be judged.

In Jura, a Delémont SME can work on a fictional supplier enquiry: extract open questions, draft a reply and identify confidential information to remove. The case separates administrative assistance from approval of an industrial commitment.

Which AI training path fits your needs?

AI on the Job — Jura
Identify a real task, write an instruction and compare the output with reference work.
Managing in the AI Era — Jura
Decide what can be assisted, who checks quality and when an error must be escalated.
Leading AI Adoption in Teams — Jura
Select a pilot use case, define evaluation criteria and organise team feedback.
Building No-Code AI Assistants and Agents — Jura
Scope an assistant, restrict its sources and permissions and test its behaviour before deployment.

Claude AI training in the canton of Jura

For Claude AI training in the canton of Jura, Claude, Anthropic’s assistant, can support a workshop when your organisation permits its use. The aim is not brand promotion: participants learn to scope a task, supply sufficient context and examine the result. Tool selection and features are confirmed during scoping according to available access.

In practice, a workshop with Claude can mean submitting a fictional dossier and requiring a sourced summary: every assertion must be traceable to the supplied documents. A quick prompt is then compared with one that specifies reader, limits and expected form, and only what is accurate is kept.

Write and refine an instruction for a workplace task.
Analyse an authorised document and verify the passages used in the answer.
Compare responses, detect omissions and correct unsupported claims.
Define human approval before reusing an output at work.

Claude is an Anthropic trademark. This page claims neither an Anthropic partnership nor an official Claude certification. No Claude subscription is advertised as included.

A learning process built around verification

Choose a real task and describe, before the exercise, what a good answer is expected to look like.
Produce a first version with the tool, on fictional data, and keep it.
Compare the result with reference documents and note gaps, omissions and additions.
Decide together what may enter daily practice and what stays restricted.

Data, errors and human supervision

Scoping sets three limits: which data may be used, which sources are authoritative, and who approves the result. Workshops handle only fictional or anonymised data. A well-written answer can be wrong; a mock-up is not a production service.

Prepare your AI training

Specify the roles involved, participants’ experience, permitted tools and a representative task. Do not send confidential documents with your enquiry. Delivery arrangements, working language and venue are agreed with SHR; a service city is not an SHR office.