Training course · Mistral Le Chat · Research & Science

Mistral Le Chat for Researchers

Mistral Le Chat as a European AI alternative: data sovereignty, agents, libraries and self-hosting options in practice.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Mistral Le Chat for Researchers” is a hands-on course for roles such as Doctoral candidates, Research associates and postdocs and Professors and research group leaders. Rather than learning Mistral Le Chat in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Research & Science.

Mistral Le Chat is the AI assistant from French provider Mistral AI and, for many organisations in the German-speaking region, an attractive European alternative to US services. Alongside familiar features such as chat, web search, document analysis, Canvas and image generation, Le Chat offers options that matter for data sovereignty: processing in Europe, business plans with administration features and models that can also run on your own infrastructure. In this practical day you first get to know Le Chat as a productive tool for writing, summarising, analysis and research in everyday work.

You then explore the features for team use: libraries, where you store your own documents as a knowledge base, agents with fixed instructions for recurring tasks, and connectors to business applications. A dedicated module puts the deployment options into perspective – from cloud service to self-hosting – and shows which questions business teams, IT and data protection should settle together. You leave with tested prompts, an agent of your own and a sound basis for deciding when Le Chat is the right choice for your organisation.

Academic work is shaped by literature reviews, data analysis, grant writing and publication pressure. Generative AI can help at every stage: navigating and summarising the literature, sharpening research questions, writing analysis code, polishing manuscripts and preparing funding applications. AI agents can automate recurring steps such as data cleaning or cross-checking references. At the same time, AI touches core questions of research integrity: who is an author, how is AI use disclosed, how do you prevent fabricated references? Researchers therefore need more than prompting tricks – they need a methodologically sound, transparent and reproducible way of working with AI tools.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Doctoral candidates
  • Research associates and postdocs
  • Professors and research group leaders
  • Research offices and grant managers
  • Corporate R&D teams

Typical challenges we address

  • An ever-growing body of literature that is hard to keep up with
  • Heavy writing load for proposals, reports and papers
  • Data analysis that requires programming skills
  • Uncertainty about AI rules set by journals, funders and universities

What you will be able to do

  • You use Le Chat productively for writing, document analysis and research in your daily work.
  • You create libraries of your own documents and use them as a reliable knowledge base.
  • You configure an agent for a recurring task and make it available to your team.
  • You evaluate cloud, business and self-hosting options from a data sovereignty perspective.
  • Use AI for literature work and writing without breaching research integrity standards.
  • Produce traceable analysis code with AI support and document it reproducibly.
  • Disclose AI use transparently in line with journal, funder and institutional requirements.

Course outline

Module 1 Le Chat at a glance and effective prompts
  • Mistral AI, its model family and positioning as a European provider
  • Le Chat features: chat, web search, Canvas, document and image analysis
  • Structuring prompts with role, context, task and output format
  • Working across languages in English, German and French
Module 2 Writing, documents and research
  • Drafting and revising emails, reports and templates
  • Uploading, summarising and querying PDFs and spreadsheets
  • Using Deep Research and web search with citations
  • Developing texts collaboratively in Canvas
Module 3 Libraries and agents
  • Creating libraries of your own documents as a knowledge base
  • Configuring agents with instructions, knowledge sources and tools
  • Testing, improving and rolling out agents to the team
  • Making sensible use of memories and connectors to business applications
Module 4 Data sovereignty and deployment options
  • Data processing, storage locations and data-usage settings
  • Cloud service, business plan and self-hosting compared
  • Open models on your own infrastructure: opportunities and effort
  • GDPR and EU AI Act requirements for tool selection
Module 5 Rollout, quality and governance
  • Assessing Le Chat fairly against other assistants
  • Checking output: verifying facts, figures and sources
  • Defining usage policies and approval processes for agents
  • Planning a pilot and making success measurable
Module 6 Practice lab: Research & Science
  • Navigating the literature
  • Sharpening research design
  • Writing analysis code
  • Revising manuscripts
  • Preparing grant proposals
  • Analysing qualitative data
Module 7 Data protection, quality & transfer to daily work
  • Codes of research integrity apply: AI cannot be an author, its use must be disclosed and all references must be checked against the original. Personal research data, for example from studies involving participants, is subject to the GDPR and ethics approvals; unpublished results and peer reviews must be treated as confidential.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Navigating the literature

AI summarises abstracts and full texts, extracts methods, samples and findings into comparison tables and helps formulate search strings for scholarly databases – every source is then verified in the original.

Sharpening research design

Research questions, hypotheses and operationalisations are stress-tested with AI as a critical sparring partner to spot gaps, confounders and alternative explanations early. Control conditions and limits to generalisability are discussed as well.

Writing analysis code

Researchers without deep programming skills use AI to produce Python or R scripts for data cleaning, statistics and visualisation, documenting them clearly to ensure reproducibility.

Revising manuscripts

AI supports language editing, structuring and shortening of academic texts, checks terminology for consistency and helps draft responses to reviewers without taking over authorship. Your argument stays your own.

Preparing grant proposals

Funding guidelines are turned into checklists, work packages and milestones are structured, and sections such as impact plans or lay summaries are drafted in several versions.

Analysing qualitative data

Interview transcripts and open-ended responses are pre-coded and grouped thematically with AI; researchers review, refine and document the coding frame according to established methodology. Inter-coder checks remain essential.

Prerequisites

Confident use of office applications and a web browser; prior AI experience is helpful but not required. No programming skills are needed for the deployment options module. Experience of academic work in a discipline; programming skills are helpful but not required.

Technical requirements

A laptop with an up-to-date browser and a Le Chat account; we recommend Pro, Team or Enterprise access to use libraries, agents and team features in full.

Data protection & compliance

Codes of research integrity apply: AI cannot be an author, its use must be disclosed and all references must be checked against the original. Personal research data, for example from studies involving participants, is subject to the GDPR and ethics approvals; unpublished results and peer reviews must be treated as confidential.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Thu, 26 November 2026 Online Request
  • Thu, 10 December 2026 Stuttgart Request
  • Wed, 13 January 2027 Berlin Request
  • Wed, 20 January 2027 Online Request
  • Mon, 25 January 2027 Munich Request
  • Tue, 2 February 2027 Online Request

Frequently asked questions

Is Mistral Le Chat automatically GDPR-compliant because Mistral is a European provider?

A European headquarters and processing in Europe make the data protection assessment easier, but they do not replace it. What counts are the contract, the data processing agreement, data-usage settings and your internal policies. In the course you learn which points to review with your data protection officer and IT before using Le Chat in production.

What does self-hosting mean with Mistral, and do I need my own IT department?

Mistral offers models and enterprise solutions that can run in your own cloud or data centre. This increases control over your data but requires infrastructure, operations and expertise. In the course we put the options into perspective so that, as a business user, you can discuss effort and benefits with your IT team on an informed basis.

Can Le Chat keep up with ChatGPT or Claude?

For many everyday office tasks – writing, summarising, research and document analysis – Le Chat delivers very good results, notably in French and German as well. Differences depend on the task, integrations and feature set. We compare typical scenarios hands-on so that you can judge its suitability for your own area yourself.

Can I use AI to write my PhD thesis?

That depends on your doctoral regulations and institutional policies. AI is often permitted for language editing and brainstorming if its use is disclosed and your own intellectual contribution remains clear. In the course you learn to document use properly and assess common grey areas with confidence.

How do I avoid fabricated references?

Language models can produce plausible-sounding citations that do not exist. Work with tools that query real databases, ask for DOIs and verify every source in the original. The course demonstrates a workflow that combines AI-assisted searching with reliable reference management.

How much does “Mistral Le Chat for Researchers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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