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curriculum [2025/10/28 15:19] – [Period 2] director-traicurriculum [2026/07/10 16:23] (current) – [Period 3] director-trai
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 ==== Period 1 ==== ==== Period 1 ====
  
-  * **Mandatory:** //Machine Learning// (MDC_51006_EP): Erwan Le Pennec and Jesse Reed, École polytechnique +  * **Mandatory:** 
-  * **Elective** (at least 1 course):+    * //Machine Learning// (MDC_51006_EP): Erwan Le Pennec and Jesse Reed, École polytechnique 
 +    * //Optimization and responsible AI for sustainability// (CSC_52073_EP): Sonia Vanier, École polytechnique 
 +    * //Adversarial AI// (APM_51181_EP):  El Mahdi El Mhamdi, École polytechnique 
 +  * **Elective** (1 course):
     * :?: //Deep Learning// (CSC_51054_EP): Michalis Vazirgiannis and Johannes Lutzeyer, École polytechnique     * :?: //Deep Learning// (CSC_51054_EP): Michalis Vazirgiannis and Johannes Lutzeyer, École polytechnique
-    * //Emerging subjects in machine learning and collaborative learning// (APM_51178_EP, research-oriented): Aymeric Dieleveut and El Mahdi El Mhamdi, École polytechnique 
     * //Signal processing from Fourier to ML// (APM_51055_EP): Rémi Flamary, École polytechnique     * //Signal processing from Fourier to ML// (APM_51055_EP): Rémi Flamary, École polytechnique
-  * **Optional:** 
-    * :!: //Statistical learning theory// (APM_51059_EP): Karim Lounici, École polytechnique 
-    * :!: //Probability theory for ML - Applications to Monte Carlo methods and generative models// (APM_51056_EP): Alain Durmus, École polytechnique 
-    * //Image analysis and computer vision// (CSC_51073_EP): Mathieu Brédif, Université Gustave Eiffel 
     * :!: //Topological data analysis// (CSC_51056_EP): Steve Oudot, INRIA     * :!: //Topological data analysis// (CSC_51056_EP): Steve Oudot, INRIA
   * Mandatory non-scientific courses:   * Mandatory non-scientific courses:
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   * **Mandatory**   * **Mandatory**
-    * //Deep Learning// (APM_52183_EP :?:): Kevin Scaman, INRIA+    * //Deep Learning// (APM_52183_EP :?:): Bruno Galerne, Université d'Orléans
     * //Reinforcement learning and autonomous agents// (CSC_52081_EP): Jesse Read, École polytechnique     * //Reinforcement learning and autonomous agents// (CSC_52081_EP): Jesse Read, École polytechnique
-  * **Elective** (1 course): 
     * //Optimization for AI// (APM_52067_EP): Luiz Chamon and Aymeric Dieuleveut, École polytechnique     * //Optimization for AI// (APM_52067_EP): Luiz Chamon and Aymeric Dieuleveut, École polytechnique
-    * //Optimization and responsible AI for sustainability// (CSC_52073_EP): Sonia Vanier, École polytechnique +  * **Elective** (2 or 3 course):
-  * **Optional** +
-    * //Statistics in action// (APM_52066_EP): Zacharie Naulet, INRAE+
     * //Advanced deep learning// (CSC_52087_EP): Vicky Kalogeiton, Johannes Lutzeyer, Ye Zhu, and Xi Wang, École polytechnique     * //Advanced deep learning// (CSC_52087_EP): Vicky Kalogeiton, Johannes Lutzeyer, Ye Zhu, and Xi Wang, École polytechnique
-    * //Introduction to text mining and NLP// (CSC_52082_EP): Davide Buscaldi, Michalis Vazirgiannis +    * //Multimodal generative AI// (CSC_52002_EP): Vicky Kalogeiton, École polytechnique
-    * //Multimodal generative AI// (CSC_52002_EP): Vicky Kalogeiton+
     * //Graph machine and deep learning for generative AI// (CSC_52072_EP): Johannes Lutzeyer and Michalis Vazirgiannis, École polytechnique     * //Graph machine and deep learning for generative AI// (CSC_52072_EP): Johannes Lutzeyer and Michalis Vazirgiannis, École polytechnique
 +    * :!: //Statistics in action// (APM_52066_EP): Zacharie Naulet, INRAE
 +    * :!: //Introduction to text mining and NLP// (CSC_52082_EP): Davide Buscaldi and Michalis Vazirgiannis, École polytechnique
   * **Mandatory non-scientific courses:**   * **Mandatory non-scientific courses:**
-    *  //Entrepreneurship for sustainability// (IME_52068_EP, Chloé Steux) **or** //Case studies on innovation// (IME_52062_EP, Philippe Ginier-Gillet)+    *  //Entrepreneurship for sustainability// (IME_52068_EP, Chloé Steux) **OR** //Case studies on innovation// (IME_52062_EP, Philippe Ginier-Gillet)
     * //Sport, Humanities, Foreign Language// (these courses are similar to those every graduate from École polytechnique must follow)     * //Sport, Humanities, Foreign Language// (these courses are similar to those every graduate from École polytechnique must follow)
  
-:?: Students must take one deep learning course that they can choose between period 1 (CSC_51054_EP) or period 2 (APM_52183_EP).+:?: Students must take one deep learning course that they can choose between period 1 (CSC_51054_EP) or period 2 (APM_52183_EP).\\ 
 +:!: Students cannot take both APM_52066_EP and CSC_52082_EP since they happen at the same time.
  
 ==== Period 3 ==== ==== Period 3 ====
  
-  * Research-oriented internship (4 to 6 months) (INT_52406_EP, 20 ECTS) +Research-oriented internship (4 to 6 months) (INT_52412_EP, 20 ECTS)
  
 \\ \\ \\ \\ \\ \\
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 ===== Second year (M2) ===== ===== Second year (M2) =====
  
 +No refresher courses are provided in the M2. All M2 courses are 24h and will credit 2 ECTS.
  
 ==== Period 1 ==== ==== Period 1 ====
  
-  +  * //Deep reinforcement learning and multi-agent systems// (CSC_53439_EP): Jesse Read, École polytechnique 
 +  * //Large language models// (CSC_53432_EP): Guokan Shang, MBZUAI 
 +  * //Privacy and uncertainty quantification// (APM_XXXX_EP): Paul Mangold, École polytechnique 
 +  * //Uncertainty quantification and Bayesian inference// (CSC_XXXX_EP) 
 +  * //Constrained (reinforcement) learning// (APM_XXXX_EP): Luiz F. O. Chamon, École polytechnique 
 +  * //Fundamentals of alignment, security, and robustness for AI// (APM_XXXX_EP): El Mahdi El Mhamdi, École polytechnique
  
 ==== Period 2 ==== ==== Period 2 ====
  
 +  * //Introduction to the verification of neural networks// (CSC_54441_EP): Eric Goubault and Sylvie Putot, École polytechnique
 +  * //Explainable AI// (APM_XXXX_EP): Marianne Clausel, University of Lorraine
 +  * //Bias and fairness// (APM_XXXX_EP): Solenne Gaucher, École polytechnique
 +  * //Explainability, security, privacy of LLMs// (CSC_XXXX_EP): Davide Buscaldi, Université Sorbonne Paris Nord
 +  * //Operational research intersects ML for explainability, sustainability, and frugality// (CSC_XXXX_EP): Sonia Vanier, École polytechnique
 +  * //Fighting disinformation and detecting fake news// (CSC_XXXX_EP): Ioana Manolescu, INRIA
  
 +==== Transverse courses and projects ====
 +**(these courses span periods 1 and 2)**
  
- +  * //Transverse project// (MDC_54430_EP, 8 ECTS): Students will work half a day per week on a project corresponding to a challenging question raised either by an industrial partner or by a researcher in the domains spanned by the program. 
-==== Transverse courses and projects (spanning periods 1 and 2) ==== +  * //Seminar on ethical issues, law and novel applications of AI// (IME_50430_EP, 6 ECTS): Véronique Steyer, École polytechnique 
- +  * **Mandatory non-scientific courses:** //Sport, Humanities, Foreign Language// (these courses are similar to those every graduate from École polytechnique must follow)
-  * Transverse project (MDC_54430_EP, 8 ECTS): Students will work half a day per week on a project corresponding to a challenging question raised either by an industrial partner or by a researcher in the domain spanned by the program. +
-  * Seminar on ethical issues, law and novel applications of AI (IME_50430_EP, 6 ECTS): Véronique Steyer, École polytechnique +
- +
-Mandatory non-scientific courses: +
-  * Sport +
-  * Humanities +
-  * Foreign Language+
  
  
 ==== Period 3 ==== ==== Period 3 ====
  
-  * Internship in an industrial or academic research lab (5 to 6 months) (INT_54490_EP, 24 ECTS)+  * Internship in an industrial or academic research lab (5 to 6 months) (INT_XXXXX_EP, 24 ECTS)
  
  
curriculum.1761664765.txt.gz · Last modified: 2025/10/28 15:19 by director-trai
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