https://www.lrde.epita.fr/index.php?title=Courses/ALSD&feed=atom&action=history
Courses/ALSD - Revision history
2024-03-29T05:28:22Z
Revision history for this page on the wiki
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https://www.lrde.epita.fr/index.php?title=Courses/ALSD&diff=124875&oldid=prev
Carlinet at 10:48, 4 February 2020
2020-02-04T10:48:43Z
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Carlinet
https://www.lrde.epita.fr/index.php?title=Courses/ALSD&diff=124857&oldid=prev
Cd at 13:15, 3 February 2020
2020-02-03T13:15:57Z
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|acronym=ALSD</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|prerequisites=Logique booléenne, Sommes (Sigma), Produits (Pi), Logarithmes</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|objectives=Ce cours présente des algorithmes et structures de données fondamentales, tout en introduisant les façons d'étudier ces algorithmes. Il s'adresse à la fois à des étudiants qui découvrent l'algorithmique qu'à des étudiants, plus informés, qui ont déjà des bases d'algorithmique mais vont apprendre à faire des calculs de complexité.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|objectives=Ce cours présente des algorithmes et structures de données fondamentales, tout en introduisant les façons d'étudier ces algorithmes. Il s'adresse à la fois à des étudiants qui découvrent l'algorithmique qu'à des étudiants, plus informés, qui ont déjà des bases d'algorithmique mais vont apprendre à faire des calculs de complexité.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|content=* Rappel des notions mathématiques utilisées par la suite.* Introduction aux mesures de complexité (notations, théorème général, exemples du tri par insertion et du tri fusion)* Autres tri comparatifs (selection, tri par tas, tri rapide, tri introspectif)* Borne de complexité des tris comparatifs* Tris linéaires* Rangs et médians (min/max, sélection stochastique, sélection en O(n))* Structure de données classiques (tableaux statiques et dynamiques, listes, piles, files, files de priorité, arbres, B-arbres)* Structures associatives (tables de hachage, arbre binaires de recherche, arbre rouge et noir, skip lists)</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|content=* Rappel des notions mathématiques utilisées par la suite.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Introduction aux mesures de complexité (notations, théorème général, exemples du tri par insertion et du tri fusion)</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Tris linéaires</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|references=Introduction to algorithms. Cormen, Leiserson, Rivest and Stein.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|references=Introduction to algorithms. Cormen, Leiserson, Rivest and Stein.</div></td>
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Cd
https://www.lrde.epita.fr/index.php?title=Courses/ALSD&diff=101087&oldid=prev
Renault at 12:55, 15 December 2016
2016-12-15T12:55:10Z
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Renault
https://www.lrde.epita.fr/index.php?title=Courses/ALSD&diff=8398&oldid=prev
Adl at 15:47, 1 July 2014
2014-07-01T15:47:30Z
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Adl
https://www.lrde.epita.fr/index.php?title=Courses/ALSD&diff=8249&oldid=prev
Daniela: Created page with "{{Course |title=Algorithmique et Structure de Données |acronym=ALSD |teacher=Adl |period=S1, App1 |audience=Apprentis |optional course=non |module=Informatique Fondamentale |..."
2014-06-10T15:05:44Z
<p>Created page with "{{Course |title=Algorithmique et Structure de Données |acronym=ALSD |teacher=Adl |period=S1, App1 |audience=Apprentis |optional course=non |module=Informatique Fondamentale |..."</p>
<p><b>New page</b></p><div>{{Course<br />
|title=Algorithmique et Structure de Données<br />
|acronym=ALSD<br />
|teacher=Adl<br />
|period=S1, App1<br />
|audience=Apprentis<br />
|optional course=non<br />
|module=Informatique Fondamentale<br />
|prerequisites=Logique booléenne, Sommes (Sigma), Produits (Pi), Logarithmes<br />
|objectives=Ce cours présente des algorithmes et structures de données fondamentales, tout en introduisant les façons d'étudier ces algorithmes. Il s'adresse à la fois à des étudiants qui découvrent l'algorithmique qu'à des étudiants, plus informés, qui ont déjà des bases d'algorithmique mais vont apprendre à faire des calculs de complexité.<br />
|content=* Rappel des notions mathématiques utilisées par la suite.<br />
* Introduction aux mesures de complexité (notations, théorème général, exemples du tri par insertion et du tri fusion)<br />
* Autres tri comparatifs (selection, tri par tas, tri rapide, tri introspectif)<br />
* Borne de complexité des tris comparatifs<br />
* Tris linéaires<br />
* Rangs et médians (min/max, sélection stochastique, sélection en O(n))<br />
* Structure de données classiques (tableaux statiques et dynamiques, listes, piles, files, files de priorité, arbres, B-arbres)<br />
* Structures associatives (tables de hachage, arbre binaires de recherche, arbre rouge et noir, skip lists)<br />
|references=Introduction to algorithms. Cormen, Leiserson, Rivest and Stein.<br />
}}</div>
Daniela