Course description
Title of the Teaching Unit
Deep Learning and generative AI
Code of the Teaching Unit
22MQ092
Academic year
2026 - 2027
Cycle
Number of credits
5
Number of hours
60
Quarter
1
Weighting
Site
Anjou
Teaching language
French
Teacher in charge
Objectives and contribution to the program
This module covers deep learning techniques.
By the end of the course, students will be able to select and implement the deep learning techniques required to automate a practical problem drawn from the real world of economics.
Prerequisites and corequisites
Data Science for Business , Machine Learning for Business
Content
1) Fundamentals of Deep Learning:
- Neural networks
- Tensors
- Optimisation algorithms
- Hyperparameters
- Training and testing
2) Image processing
- Convolutional networks
- Case studies
- Object detection
- Facial recognition
3) LLM
- Recurrent neural networks (RNNs)
- NLP and word embeddings
- Sequence models
- Transformers
Teaching methods
- Lectures and practical sessions in the laboratory using specialist software
- Practical case studies
Assessment method
The examination will be oral and will include, amongst other things, the presentation and defence of a group project.