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--- start [2024/07/15 09:48] – 193.32.126.233
+++ start [2024/10/28 13:33] (current) – respai-vic
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 ==== Motivation ====
-In the intersection of Computer Science and Applied Mathematics, **Artificial Intelligence (AI)** is a steadily growing field generating a wealth of impressive achievements. The goal of AI is to develop intelligent systems able to help with complex tasks. This requires knowledge and reasoning, and in recent years also includes learning from data. The field of AI is currently progressing at a rapid speed. This has led to growing societal impact and an ever-increasing academic and industrial interest, even more so with the emergence of generative AI. With the pervasive use of AI methods, improving their reliability and robustness as well as accounting for their ethical and legal aspects have become mandatory.
+In the intersection of Computer Science and Applied Mathematics, **Artificial Intelligence (AI)** is a steadily growing field generating a wealth of impressive achievements. The goal of AI is to develop intelligent systems able to help with complex tasks. This requires knowledge and reasoning, and in recent years also includes learning from data. The field of AI is currently progressing at a rapid speed. This has led to growing societal impact and an ever-increasing academic and industrial interest, even more so with the emergence of generative AI. Due to the pervasive use of AI methods, improving their reliability and robustness as well as accounting for their ethical and legal aspects have become mandatory.
 Combined with **Visual Computing (ViC)** techniques, a part of Computer Science that studies the processing and simulation of visual information in all its forms (from text, graphs, sound, images and videos to 3D virtual worlds), Artificial Intelligence leads to strong societal impact applications, such as for instance:
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-==== Curriculum description  ====
+==== Curriculum Description  ====
 The first week consists of refresher courses in mathematics (statistical analysis, introduction to Machine Learning) and Computer Science (C++ programming, basics of 3D modeling and algorithmic geometry), to complement the existing academic background of the students.
-It will be followed by two training periods of 2.5 months, consisting of courses on the following topics **(detailed version [[curriculum|here]])** :
+It will be followed by two training periods of 2.5 months, consisting of courses on the following topics **(detailed version [[https://msct.dix.polytechnique.fr/aivic/wiki/doku.php?id=curriculum|here]])** :
   * Deep Learning, Generative AI and Reinforcement learning
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-==== Industrial Partnership / Cercle des partenaires ====
+==== Industrial & Institutional Partnership / Cercle des partenaires ====
-Our MScT is accompanied by an active group of industrial partners contributing both student grants and transverse projects, as well as student internships. Some in the past, some currently, these partners include Inria, Google, Enedis, Idemia, as well as, younger companies such as Anatoscope, Homiwoo, InitML, and Gojob.
+Our MScT is accompanied by an active group of industrial and institutional partners contributing both student grants and transverse projects, as well as student internships. Some in the past, some currently, these partners include Inria, Google, Enedis, Idemia, Helsing as well as, younger companies such as Anatoscope, Homiwoo, InitML and Wemap.
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-Students have the option to either find their own internship position or to choose one of the internship proposals that we make available to them.
+Students have the option to either find their own internship position or to choose one of the internship proposals that we have made available **[[https://msct.dix.polytechnique.fr/aivic/wiki/doku.php?id=internships|here]]** and are regularly updating.