• Understand the capabilities of Mistral language models in a professional context.
• Identify the use cases relevant to the business.
• Plan and deploy AI projects based on Mistral models.
• Analyze the return on investment (ROI) of AI solutions.

Morning: understand and explore Mistral

1: Introduction to language models

• Understand language models (LLM) and their role.
• Specificities of Mistral models: architecture, performances, use cases.
• Comparison with other AI solutions on the market.

2: Mistral's capabilities for the business

• Use cases in different sectors (health, finance, industry, retail).
• Key features: automation, text analysis, content creation, etc.
• Practical workshop: exploration of pre-configured examples on Mistral.

3: Technical demonstration

• Use of the Mistral interface: access, handling and configuration.
• Live demonstration: text generation, sentiment analysis, information extraction.
• Practical case : put into practice.

Afternoon: setting up an AI project with Mistral

1: Identify opportunities and risks

• Business needs analysis: where and how AI can be integrated.
• Risk identification: model bias, data security, regulations (RGPD).
• Good practices for ethical and responsible use.

2: Integrating Mistral into existing systems

• Tools and infrastructures required to deploy Mistral.
• Integration with other technologies: CRM, ERP, ERP, databases, API.
• Practical case : design of an integration architecture.

3: ROI planning and measurement

• Methods for evaluating the costs and benefits of AI projects.
• Key performance indicators (KPIs) to measure effectiveness.
• Practical case : simulation of a profitability study.