Train in AI with EFELIA Côte d'Azur
We offer you a range of professional training menus tailored to your needs and aimed at a variety of audiences. You can benefit from preparation and upgrading if necessary, depending on the menu chosen (programming and databases, statistics, etc.).
Our AI specialists aim to provide you with the most comprehensive training possible: 50% theory and 50% practice.
Fritzchens Fritz / Better Images of AI / GPU shot etched 1 / CC-BY 4.0
Professional training menu 1: Deep Learning
Public: academic, non-engineer or engineer, bac+5 level
Content:
- Half-day 1: Intro to AI panorama - Knowledge representation and ML
- Half-day 2: Pattern recognition (MLP) and word representation - Auto-encoders, dimension reduction, DAE or VAE, self-supervised, IAT bias
- Half-day 3: Text generation (RNN and Transformer light) and ChatGPT, issues at stake
- Half-Day 4: Knowledge representation - Knowledge graphs, ontologies, multi-agent systems
Professional training menu 2: Introduction to AI
Public: non-engineers or engineers, bac+5 level
Content:
Basics and general principles
- Day 1: Introduction to AI
- Day 2: Pattern recognition (MLP) and word representation
- Day 3: Text generation and ChatGPT
- Day 4: Knowledge representation
- Day 5: Societal, legal and economic issues
- Day 6: Convolutional neural networks (CNN) and recurrent neural networks (RNN)
- Day 7: Transformer networks for text and vision
- Day 8: Dimension reduction (PCA, auto-encoders, VAE) and generative methods
- Day 9: Structured data: rule inference, structured data classification (GBM)
- Day 10: Knowledge graphs and inference
Professional training menu 3: Introduction to AI
Public: academic, non-engineer or engineer, bac+5 level
Content:
Content:
- Half-day 1: Intro to AI panorama - Knowledge representation and ML
- Half-day 2: Pattern recognition (MLP) and word representation - Auto-encoders, dimension reduction, DAE or VAE, self-supervised, IAT bias
- Half-day 3: Text generation (RNN and Transformer light) and ChatGPT, issues at stake
- Half-Day 4: Knowledge representation - Knowledge graphs, ontologies, multi-agent systems
For further information, please contact our team by e-mail (EFELIA.formation@univ-cotedazur.fr).