3IA-EFELIA Côte d'Azur: Training courses for every company
- For every type of audience, technical or non-technical, of every corporation:
- advanced in AI
- in transition to AI
- Customisable training menus:
- 1 to 5 day programmes
- With or without practice
- Adaptable to focus on AI methods and applications targeted by the company
- In English or French
- Taught by recognised academic excellence: 3IA researchers
- Ongoing sessions for: STMicroelectronics, Ecole de l'Air ...
For more information, contact us at violette.assati@univ-cotedazur.fr.
Customisable training menus for companies
Consult the training catalog
- Introduction to Artificial Intelligence 1
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- Overview and principles of approaches
- ChatGPT, opportunities across various domains
- Ethical, legal and societal issues
Target audience: Non-engineers or engineers, all levels, all professions
Duration: 3 to 9 hours
- Introduction to Artificial Intelligence 2
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- Overview of methodological approaches in AI (data mining, data science, machine learning, artificial neural networks)
- Pattern recognition, dimension reduction and generative methods
- Text generation, ChatGPT, uses and prompt engineering
- Knowledge representation
- Structured data and rule inference
Target audience: Engineers
Duration: 12 to 30 hours
- Statistical Learning
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- Statistical foundations and machine learning
- Statistics in large dimensions
- Small sample statistics
- Statistics for missing data
Target audience: Non-engineers or engineers with master degree or equivalent
Duration: 12 to 24 hours
- Deep Learning
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- Introduction to machine learning and deep learning
- Deep learning for vision (CNN)
- Deep learning for text (Transformers)
- Generative methods
Target audience: Engineers
Duration: 12 to 30 hours (2 to 5 days)
- Generative AI 1
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- Foundation models, Prompt engineering
- Opportunities and challenges for companies (programming, HR, etc.)
Target audience: Non-engineers or engineers with master degree or equivalent
Duration: 3 to 9 hours
- Generative AI 2
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- Transformers, Foundation models and adaptation: fine-tuning, prompt engineering, prompt tuning
- Resources, performance analysis, biases
- Limits and challenges for research and innovation
Target audience: Engineers
Duration: 6 to 12 hours