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as envie de te lancer dans une carri\u00e8re en data science, mais tu ne sais pas par o\u00f9 commencer ? D\u00e9couvre les 5 conseils des professeurs du Wagon : des pr\u00e9-requis, aux fondamentaux tu seras fin pr\u00eat.e pour te lancer sereinement dans ces 9 semaines intensives !","_yoast_wpseo_title":"5 conseils pour se pr\u00e9parer au bootcamp Data Science | Le Wagon","contenu_de_larticle":"

La formation en Data Science<\/a> du Wagon a pour objectif de te donner toutes les comp\u00e9tences n\u00e9cessaires pour te former aux m\u00e9tiers de la Data Science<\/a> et lancer ta carri\u00e8re dans une \u00e9quipe Data. Des fondamentaux de Pandas aux mod\u00e8les avanc\u00e9s de Deep Learning, tu apprendras \u00e0 explorer, nettoyer, transformer des donn\u00e9es de A \u00e0 Z, en travaillant en \u00e9quipe avec les meilleurs outils. Mais pour \u00eatre pr\u00eat.e. \u00e0 100% il y a quelques pr\u00e9-requis que nous te livrons ici ! 


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Conseil n\u00b01 : Revoir le programme de maths de Terminale S 

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Il est essentiel pour un.e data analyst<\/a> d'avoir au minimum des notions de calculs statistiques et d'alg\u00e8bre lin\u00e9aire. Ces connaissances permettent de d\u00e9terminer la bonne technique d'approche et d'analyse pour chaque donn\u00e9e.<\/strong> Il faut donc que tu te replonges dans le programme math\u00e9matique et algorithmique de terminale S : les fonctions<\/a>, leurs d\u00e9riv\u00e9es<\/a> & leur syst\u00e8me d'\u00e9quations lin\u00e9aires<\/a>. mais aussi calcul<\/a>, alg\u00e8bre lin\u00e9aire<\/a> et statistiques<\/a> ne doivent plus avoir de secret pour toi ! N'h\u00e9sites pas non plus \u00e0 aller plus loin si tu le souhaites, ta compr\u00e9hension intuitive du Machine Learning n'en sera qu'am\u00e9lior\u00e9e.<\/div>
 

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Conseil n\u00b02 : S\u2019exercer au code avec Python

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Les postes de data analysts requi\u00e8rent la ma\u00eetrise d\u2019au moins un langage de programmation. Le langage le plus couramment employ\u00e9 est Python<\/strong>. Nous te recommandons donc de mettre les mains dans le cambouis et de commencer \u00e0 coder d\u00e8s que tu peux gr\u00e2ce aux diff\u00e9rentes tracks Python qui existent. Tu dois \u00eatre \u00e0 l'aise avec les types de donn\u00e9es et les variables, les conditions, les boucles, les fonctions et les deux structures de donn\u00e9es list & dict (nomm\u00e9es Array et Hash en Ruby). N'h\u00e9site pas \u00e0 te lancer ici<\/a> d\u00e8s aujourd\u2019hui ! 

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Conseil n\u00b03 : Suivre et terminer le prep work

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Si tu as pass\u00e9 un entretien avec notre super admission manager, Laura, et que tu as termin\u00e9 le processus de s\u00e9lection c'est que tu es pr\u00eat \u00e0 continuer l\u2019aventure Wagon. Le moment est venu de passer aux choses s\u00e9rieuses : nous t'avons concoct\u00e9 un travail pr\u00e9paratoire \u00e0 faire en ligne pour t'immerger encore plus dans la Data Science. Cette track dure environ 40 heures et couvre les bases de la programmation avec Python et SQL ainsi que certains concepts cl\u00e9s utilis\u00e9s quotidiennement par les data analysts. Ce travail pr\u00e9paratoire est obligatoire<\/strong> et doit \u00eatre effectu\u00e9 avant le d\u00e9but du bootcamp.


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Conseil n\u00b04 : Appr\u00e9hender sa machine

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L'ordinateur est au data scientist<\/a> ce que le pinceau est au peintre. Prenez le temps de vous familiariser avec votre machine : raccourcis clavier, outils de prise de notes rapide, \u00e9diteur de texte comme SublimeText, arborescence des fichiers, commandes de base dans le terminal, autant d'automatismes qui vous feront gagner du temps et arriver 100% pr\u00eat pour le bootcamp  <\/div>

Kevin, Bruno et Benjamin, professeurs de la formation en Data Science<\/figcaption><\/figure><\/a>

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Conseil n\u00b05 : Se reposer pour arriver frais et dispo

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Le Wagon est un sprint de 9 semaines. Un rythme soutenu, un apprentissage continu et une exp\u00e9rience humaine intense. Il n'est pas impossible que tu r\u00eaves de de Jupyter Notebook pendant tes premi\u00e8res semaines de bootcamp. Alors pour tenir sur la dur\u00e9e, m\u00e9nager ton corps et tes m\u00e9ninges et travailler ta concentration, prends du temps pour toi, ta famille et tes amis avant de te lancer dans l'aventure. 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