Deep Learning School 2025

The Deep Learning School at Université Côte d'Azur is a major scientific event for the research and engineering communities working at the frontline of AI. Since 2017, we have provided our extended ecosystem with the opportunity to learn from prestigious AI researchers and practicing the latest techniques in hands-on sessions with local expert supervisors.
 

Whether you are a researcher, an engineer, an expert in deep learning, or simply eager to learn more about these crucial methods at the core of modern AI, this program is designed for you!
 

The DLS 2025 prestigious lineup


Prof. Zeynep Akata
Technical University of Munich

Prof. Yulan He
King's College London

Prof. Dan Jurafsky
Stanford University

Prof. Stuart Russell
UC Berkeley

Prof. Mihaela Van der Schaar
University of Cambridge

 

Practical information

  • When?

June 23rd, 2025 to July 4th, 2025

  • Where?

Campus SophiaTech, Sophia Antipolis

  • Language

English

  • Target audience

Engineers, master and doctorate students, researchers

  • Pre-requisite 

▸ Master of science
▸ If you do not have strong background and practive in machine learning, you are strongly advised to register to tutorials, additionally to conferences
▸ Being currently employ or seeking a job

Registration

Please do provide any useful information allowing us to identify which category of registration fees applies to your case.
External companies / Individuals

Price per week (tutorials and conferences): 900 €
Price per week (conferences only): 500 €

Register

Partnering companies / Individuals

Price per week (tutorials and conferences): 810 €
Price per week (conferences only): 450 €

Register

External academic staff

Price per week (tutorials and conferences): 630 €
Price per week (conferences only): 350 €

Register

Academic staff from EFELIA Côte d’Azur consortium

Price per week (tutorials and conferences): 220 €
Price per week (conferences only): 220 €

Register

Week 1
Tutorials: Monday and Tuesday
Conferences: Wednesday, Thursday, and Friday

Week 2
Tutorials: Monday and Tuesday
Conferences: Wednesday, Thursday, and Friday

Prices include lectures with labs or tutorials with labs for each day.

Detailed program

 
Monday, June 23

Tutorial and lab: Build your own LLM from Scratch  

  • Morning: Refresher Pytorch, Multi-Layer Perceptron, Recurrent Neural Network, applied to Natural Language Processing
  • Afternoon: Tokenizer, Text embedding, Attention

Speakers: Prof. Frederic Precioso & Team EFELIA Côte d'Azur

Tuesday, June 24

Tutorial and lab: Build your own LLM from Scratch

  • Morning: Transformer-Encoder, Attention, Multi-Head Attention
  • Afternoon: LLM(Encoder) for Text Classification, for Image + Text classification

Speakers: Prof. Frederic Precioso & Team EFELIA Côte d'Azur

Wednesday, June 24
  • Speaker: Hugging Face
  • Topic: Ultra-Scale Playbook and Small Language Models
Thursday, June 24
  • Speaker: Prof. Mihaela van der Schaar, University of Cambridge (UK)
  • Topic: Machine Learning and Data-centric AI for Healthcare and Medecine
Friday, June 24

More info to come

Monday, June 30

Tutorial and lab: Build your own LLM from Scratch

  • Morning: Transformer-Decoder, Masked Multi-Head Attention, LLM(Decoder) for Text generation
  • Afternoon: LLM(Encoder-Decoder), Cross-Attention, for Translation, Summarization

Speakers: Prof. Frederic Precioso & Team EFELIA Côte d'Azur

Tuesday, July 1st

Tutorial and lab: Build your own LLM from Scratch

  • Morning: Reinforcement Learning, Reinforcement Learning from Human Feedback (RLHF)
  • Afternoon: Use case DeepSeek R1  

Speakers: Prof. Frederic Precioso & Team EFELIA Côte d'Azur

Wednesday, July 2nd
  • Speaker: Prof. Yulan He, King’s College London (UK)
  • Topic: Self-evolution of large language models (LLMs)
Thursday, July 3rd
  • Speaker: Prof. Zeynep Akata, Technical University of Munich (Germany)
  • Topic: Vision Language Models and General Knowledge Transfer 
Friday, July 4th
  • Morning

Prof. Stuart Russell, University of California at Berkeley (USA)
Topic: From Reinforcement Learning from Human Feedback for LLMs to Assistance Games  

  • Afternoon

Prof. Dan Jurafsky, Stanford University (USA)
Topic: LLMs assessment, Ethics