{"id":90698,"date":"2020-08-05T01:42:04","date_gmt":"2020-08-04T23:42:04","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/bystryj-start-i-nizkij-potolok-chto-zhdet-molodyh-data-science-speczialistov-na-rynke-truda"},"modified":"2020-08-05T01:42:04","modified_gmt":"2020-08-04T23:42:04","slug":"bystryj-start-i-nizkij-potolok-chto-zhdet-molodyh-data-science-speczialistov-na-rynke-truda","status":"publish","type":"post","link":"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/bystryj-start-i-nizkij-potolok-chto-zhdet-molodyh-data-science-speczialistov-na-rynke-truda","title":{"rendered":"Rychl\u00fd start a n\u00edzk\u00fd limit. Co \u010dek\u00e1 mlad\u00e9 odborn\u00edky na Data Science na trhu pr\u00e1ce","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Podle v\u00fdzkum\u016f HeadHunter a Mail.ru popt\u00e1vka po odborn\u00edc\u00edch v oboru Data Science p\u0159evy\u0161uje nab\u00eddku, ale i tak se mlad\u00fdm specialist\u016fm ne v\u017edy poda\u0159\u00ed naj\u00edt pr\u00e1ci. \u0158\u00edk\u00e1me si, co absolvent\u016fm kurz\u016f chyb\u00ed a kde se mohou u\u010dit ti, kte\u0159\u00ed pl\u00e1nuj\u00ed velkou kari\u00e9ru v Data Science.<\/p>\n<blockquote><p>\u201eP\u0159ich\u00e1zej\u00ed a mysl\u00ed si, \u017ee te\u010f budou vyd\u011bl\u00e1vat 500k za sekundu, proto\u017ee znaj\u00ed n\u00e1zvy framework\u016f a jak z nich spustit model ve dvou \u0159\u00e1dc\u00edch\u201c<\/p><\/blockquote>\n<p>\n<b>Emil Mageramov<\/b> vede skupinu slu\u017eeb v\u00fdpo\u010detn\u00ed chemie ve spole\u010dnosti biocad a na pohovorech se setk\u00e1v\u00e1 s t\u00edm, \u017ee kandid\u00e1ti nemaj\u00ed systematick\u00e9 pochopen\u00ed profese. Dokon\u010d\u00ed kurzy, p\u0159ich\u00e1zej\u00ed s dob\u0159e rozvinut\u00fdmi dovednostmi v Pythonu a SQL, mohou za 2 vte\u0159iny spustit Hadoop nebo Spark, splnit \u00fakol podle p\u0159esn\u00e9ho zad\u00e1n\u00ed. Ale ud\u011blat krok stranou \u2014 to u\u017e ne. P\u0159itom pr\u00e1v\u011b flexibilitu \u0159e\u0161en\u00ed zam\u011bstnavatel\u00e9 o\u010dek\u00e1vaj\u00ed od sv\u00fdch specialist\u016f v oblasti Data Science.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h3>Co se d\u011bje na trhu Data Science<\/h3>\n<p>\nKompetence mlad\u00fdch specialist\u016f odr\u00e1\u017e\u00ed stav na trhu pr\u00e1ce. Zde popt\u00e1vka v\u00fdrazn\u011b p\u0159evy\u0161uje nab\u00eddku, proto bezradn\u00ed zam\u011bstnavatel\u00e9 jsou \u010dasto skute\u010dn\u011b ochotni p\u0159ij\u00edmat zcela nezku\u0161en\u00e9 specialisty a vychovat je podle sebe. Tato varianta funguje, ale je vhodn\u00e1 pouze v p\u0159\u00edpad\u011b, \u017ee v t\u00fdmu ji\u017e je zku\u0161en\u00fd teamlead, kter\u00fd p\u0159evezme \u0161kolen\u00ed juniora.<\/p>\n<p>Podle v\u00fdzkumu HeadHunter a Mail.ru jsou odborn\u00edci na anal\u00fdzu dat jedni z nej\u017e\u00e1dan\u011bj\u0161\u00edch na trhu:<\/p>\n<ul>\n<li>V roce 2019 vzrostl po\u010det pracovn\u00edch m\u00edst v oblasti anal\u00fdzy dat 9,6kr\u00e1t, zat\u00edmco v oblasti strojov\u00e9ho u\u010den\u00ed \u2013 7,2kr\u00e1t, ve srovn\u00e1n\u00ed s rokem 2015.<\/li>\n<li>Ve srovn\u00e1n\u00ed s rokem 2018 se po\u010det pracovn\u00edch m\u00edst pro specialisty na anal\u00fdzu dat zv\u00fd\u0161il 1,4kr\u00e1t, pro strojov\u00e9 u\u010den\u00ed \u2013 1,3kr\u00e1t.<\/li>\n<li>38% otev\u0159en\u00fdch pracovn\u00edch m\u00edst p\u0159ipad\u00e1 na IT spole\u010dnosti, 29% \u2014 spole\u010dnosti z finan\u010dn\u00edho sektoru, 9% \u2014 oblast slu\u017eeb pro podnik\u00e1n\u00ed.<\/li>\n<\/ul>\n<p>\nSituaci podn\u011bcuj\u00ed \u010detn\u00e9 online \u0161koly, kter\u00e9 \u0161kol\u00ed pr\u00e1v\u011b ty juniory. V\u011bt\u0161inou se v\u00fduka kon\u00e1 od t\u0159\u00ed do \u0161esti m\u011bs\u00edc\u016f, b\u011bhem nich\u017e se studenti na z\u00e1kladn\u00ed \u00farovni nau\u010d\u00ed hlavn\u00ed n\u00e1stroje: Python, SQL, anal\u00fdzu dat, Git a Linux. V\u00fdsledkem je klasick\u00fd junior: dok\u00e1\u017ee vy\u0159e\u0161it konkr\u00e9tn\u00ed \u00fakol, ale ch\u00e1pat probl\u00e9m a samostatn\u011b formulovat \u00fakol je\u0161t\u011b neum\u00ed. Vysok\u00e1 popt\u00e1vka po odborn\u00edc\u00edch a humbuk kolem profese v\u0161ak \u010dasto vyvol\u00e1v\u00e1 vysok\u00e9 ambice a po\u017eadavky na mzdu.<\/p>\n<blockquote><p>Bohu\u017eel, pohovor na pozici Data Scientist obvykle vypad\u00e1 takto: kandid\u00e1t \u0159\u00edk\u00e1, \u017ee se pokusil pou\u017e\u00edt p\u00e1r knihoven, na ot\u00e1zky o tom, jak p\u0159esn\u011b funguj\u00ed algoritmy, nedok\u00e1\u017ee odpov\u011bd\u011bt, a pot\u00e9 si \u017e\u00e1d\u00e1 200, 300, 400 tis\u00edc rubl\u016f m\u011bs\u00ed\u010dn\u011b na ruku.<\/p>\n<p>Kv\u016fli velk\u00e9mu mno\u017estv\u00ed reklamn\u00edch slogan\u016f jako \"sta\u0148te se datov\u00fdm analytikem m\u016f\u017ee ka\u017ed\u00fd\", \"nau\u010dte se strojov\u00e9 u\u010den\u00ed za t\u0159i m\u011bs\u00edce a za\u010dn\u011bte vyd\u011bl\u00e1vat spoustu pen\u011bz\" a touze po rychl\u00e9m zisku do na\u0161\u00ed oblasti p\u0159i\u0161el obrovsk\u00fd proud povrchn\u00edch kandid\u00e1t\u016f, kte\u0159\u00ed nemaj\u00ed \u017e\u00e1dnou systematickou p\u0159\u00edpravu.<\/p>\n<p><b>Viktor Kantor<\/b><br \/>\nChief Data Scientist ve MTS<\/p><\/blockquote>\n<p><\/p>\n<h3>Koho cht\u011bj\u00ed zam\u011bstnavatel\u00e9<\/h3>\n<p>\nKa\u017ed\u00fd zam\u011bstnavatel by cht\u011bl, aby jeho junio\u0159i pracovali bez neust\u00e1l\u00e9ho dohledu a mohli se rozv\u00edjet pod veden\u00edm t\u00fdmov\u00e9ho leadra. K tomu mus\u00ed nov\u00e1\u010dek hned ovl\u00e1dat pot\u0159ebn\u00e9 n\u00e1stroje, aby \u0159e\u0161il aktu\u00e1ln\u00ed \u00fakoly, a m\u00edt dostate\u010dn\u00e9 teoretick\u00e9 znalosti, aby postupn\u011b navrhoval vlastn\u00ed \u0159e\u0161en\u00ed a p\u0159istupoval k slo\u017eit\u011bj\u0161\u00edm zad\u00e1n\u00edm.<\/p>\n<p>S n\u00e1stroji jsou nov\u00e1\u010dci na trhu docela v po\u0159\u00e1dku. Kr\u00e1tkodob\u00e9 kurzy umo\u017e\u0148uj\u00ed rychle je ovl\u00e1dnout a za\u010d\u00edt pracovat.<\/p>\n<p>Podle v\u00fdzkumu HeadHunter a Mail.ru je nej\u017e\u00e1dan\u011bj\u0161\u00ed dovednost\u00ed znalost Pythonu. Ta je zm\u00edn\u011bna v 45 % nab\u00eddek pracovn\u00edch pozic specialist\u016f na anal\u00fdzu dat a ve 51 % nab\u00eddek v oblasti strojov\u00e9ho u\u010den\u00ed.<\/p>\n<p>Zam\u011bstnavatel\u00e9 tak\u00e9 cht\u011bj\u00ed, aby specialist\u00e9 na anal\u00fdzu dat um\u011bli SQL (23 %), m\u011bli znalosti z oblasti inteligentn\u00ed anal\u00fdzy dat (DataMining) (19 %), statistick\u00e9 matematiky (11 %) a um\u011bli pracovat s velk\u00fdmi daty (10 %).<\/p>\n<p>Zam\u011bstnavatel\u00e9, kte\u0159\u00ed hledaj\u00ed specialisty na strojov\u00e9 u\u010den\u00ed, vedle znalosti Pythonu o\u010dek\u00e1vaj\u00ed, \u017ee kandid\u00e1t bude ovl\u00e1dat C++ (18 %), SQL (15 %), algoritmy strojov\u00e9ho u\u010den\u00ed (13 %) a Linux (11 %).<\/p>\n<p>Ale pokud jsou n\u00e1stroje pro juniory v po\u0159\u00e1dku, jejich nad\u0159\u00edzen\u00ed se pot\u00fdkaj\u00ed s jin\u00fdm probl\u00e9mem. V\u011bt\u0161ina absolvent\u016f kurz\u016f nem\u00e1 hlubok\u00e9 porozum\u011bn\u00ed profesi, tak\u017ee nov\u00e1\u010dkovi se obt\u00ed\u017en\u011b postupuje.<\/p>\n<blockquote><p>Nyn\u00ed hled\u00e1m specialisty na strojov\u00e9 u\u010den\u00ed do sv\u00e9ho t\u00fdmu. P\u0159itom vid\u00edm, \u017ee \u010dasto kandid\u00e1ti ovl\u00e1dli jednotliv\u00e9 n\u00e1stroje Data Science, ale chyb\u00ed jim dostate\u010dn\u00e9 hlubok\u00e9 porozum\u011bn\u00ed teoretick\u00fdm z\u00e1klad\u016fm pro vytv\u00e1\u0159en\u00ed nov\u00fdch \u0159e\u0161en\u00ed.<\/p>\n<p><b>Emil Mageramov<\/b><br \/>\nVedouc\u00ed skupiny slu\u017eeb v\u00fdpo\u010detn\u00ed chemie, Biocad\n<\/p><\/blockquote>\n<p> Samotn\u00e1 struktura a d\u00e9lka kurz\u016f neumo\u017e\u0148uj\u00ed hloub\u011bji proniknout na pot\u0159ebnou \u00farove\u0148. Absolvent\u016fm \u010dasto chyb\u00ed pr\u00e1v\u011b ty soft skills, kter\u00e9 se obvykle opom\u00edjej\u00ed p\u0159i \u010dten\u00ed pracovn\u00edch nab\u00eddek. Kdo z n\u00e1s by ale \u0159ekl, \u017ee nem\u00e1 syst\u00e9mov\u00e9 my\u0161len\u00ed nebo chu\u0165 se rozv\u00edjet. Nicm\u00e9n\u011b co se t\u00fd\u010de specialisty Data Science, jde o mnohem hlub\u0161\u00ed z\u00e1le\u017eitost. Aby se rozv\u00edjeli, pot\u0159ebuj\u00ed dostate\u010dn\u011b siln\u00fd sklon k teorii a v\u011bd\u011b, co\u017e je mo\u017en\u00e9 pouze p\u0159i del\u0161\u00edm studiu, nap\u0159\u00edklad na univerzit\u011b.<\/p>\n<blockquote><p>Mnoho z\u00e1le\u017e\u00ed na \u010dlov\u011bku: pokud t\u0159\u00ed m\u011bs\u00ed\u010dn\u00ed intenzivn\u00ed kurz od siln\u00fdch lektor\u016f s zku\u0161enostmi z veden\u00ed t\u00fdm\u016f v p\u0159edn\u00edch firm\u00e1ch absolvuje \u00fa\u010dastn\u00edk s dobrou z\u00e1kladnou v matematice a programov\u00e1n\u00ed, pono\u0159\u00ed se do v\u0161ech materi\u00e1l\u016f kurzu a \u201evsakuje jako houba\u201c, jak se \u0159\u00edkalo ve \u0161kole, pak s takov\u00fdm zam\u011bstnancem nen\u00ed pozd\u011bji probl\u00e9m. Ale 90-95% lid\u00ed pot\u0159ebuje, aby si n\u011bco osvojili nav\u017edy, nau\u010dit se desetkr\u00e1t v\u00edce a d\u011blat to systematicky n\u011bkolik let po sob\u011b. A to d\u011bl\u00e1 magistersk\u00e9 programy v anal\u00fdze dat vynikaj\u00edc\u00ed mo\u017enost\u00ed, jak z\u00edskat dobr\u00fd z\u00e1klad znalost\u00ed, se kter\u00fdm se \u010dlov\u011bk na pohovoru nemus\u00ed \u010dervenat a pr\u00e1ce bude mnohem snaz\u0161\u00ed.<\/p>\n<p><b>Viktor Kantor<\/b><br \/>\nChief Data Scientist ve MTS<\/p><\/blockquote>\n<h3>Kde se u\u010dit, abych na\u0161el pr\u00e1ci v Data Science<\/h3>\n<p>\nNa trhu je mnoho kvalitn\u00edch kurz\u016f na Data Science a z\u00edsk\u00e1n\u00ed z\u00e1kladn\u00edho vzd\u011bl\u00e1n\u00ed nen\u00ed probl\u00e9m. Ale je d\u016fle\u017eit\u00e9 ch\u00e1pat zam\u011b\u0159en\u00ed tohoto vzd\u011bl\u00e1v\u00e1n\u00ed. Pokud m\u00e1 uchaze\u010d ji\u017e siln\u00e9 technick\u00e9 z\u00e1zem\u00ed, pak intenzivn\u00ed kurzy jsou p\u0159esn\u011b to, co pot\u0159ebuje. Osoba si osvoj\u00ed n\u00e1stroje, p\u0159ijde na m\u00edsto a rychle se zapracuje, proto\u017ee u\u017e um\u00ed uva\u017eovat jako matematik, vid\u00ed probl\u00e9m a formuluje \u00fakoly. Pokud takov\u00e9 z\u00e1zem\u00ed nen\u00ed, pak po kurzu bude dobr\u00fdm vykonavatelem, ale s omezen\u00fdmi mo\u017enostmi pro r\u016fst.<\/p>\n<blockquote><p>Pokud p\u0159ed v\u00e1mi stoj\u00ed kr\u00e1tkodob\u00fd \u00fakol zm\u011bny profese nebo hled\u00e1n\u00ed pr\u00e1ce v t\u00e9to specializaci, pak v\u00e1m vyhovuj\u00ed n\u011bjak\u00e9 systematick\u00e9 kurzy, kter\u00e9 jsou kr\u00e1tk\u00e9 a rychle poskytuj\u00ed minim\u00e1ln\u00ed soubor technick\u00fdch dovednost\u00ed, abyste mohli usilovat o za\u010d\u00e1te\u010dn\u00ed pozici v t\u00e9to oblasti.<\/p>\n<p><b>Ivan Jamschikov<\/b><br \/>\nAkademick\u00fd \u0159editel online magistersk\u00e9ho programu \u201eData Science\u201c<\/p><\/blockquote>\n<p>Probl\u00e9m kurz\u016f spo\u010d\u00edv\u00e1 pr\u00e1v\u011b v tom, \u017ee poskytuj\u00ed rychl\u00e9, ale minim\u00e1ln\u00ed nastartov\u00e1n\u00ed. \u010clov\u011bk vstoup\u00ed do profese a rychle dos\u00e1hne stropu. Aby se \u010dlov\u011bk do profese dostal na dlouho, je pot\u0159eba hned polo\u017eit dobrou z\u00e1kladnu ve form\u011b dlouhodob\u011bj\u0161\u00edho programu, nap\u0159\u00edklad v magistersk\u00e9m studiu.<\/p>\n<blockquote><p>Vysoko\u0161kolsk\u00e9 vzd\u011bl\u00e1n\u00ed je vhodn\u00e9, kdy\u017e ch\u00e1pete, \u017ee v\u00e1s tato oblast zaj\u00edm\u00e1 dlouhodob\u011b. Netou\u017e\u00edte co nejd\u0159\u00edve nastoupit do zam\u011bstn\u00e1n\u00ed. A nechcete m\u00edt kari\u00e9rn\u00ed strop, tak\u00e9 nechcete \u010delit probl\u00e9mu nedostatku znalost\u00ed, dovednost\u00ed, nedostatku porozum\u011bn\u00ed celkov\u00e9 ekosyst\u00e9mu, s jeho\u017e pomoc\u00ed se vyv\u00edjej\u00ed inovativn\u00ed produkty. K tomu je pot\u0159eba pr\u00e1v\u011b vysoko\u0161kolsk\u00e9 vzd\u011bl\u00e1n\u00ed, kter\u00e9 formuje nejen pot\u0159ebnou sadu technick\u00fdch dovednost\u00ed, ale tak\u00e9 strukturuje va\u0161e my\u0161len\u00ed a pom\u00e1h\u00e1 formulovat ur\u010dit\u00e9 vid\u011bn\u00ed va\u0161\u00ed kari\u00e9ry na del\u0161\u00ed \u010dasov\u00e9 obdob\u00ed.<\/p>\n<p><b>Ivan Jamschikov<\/b><br \/>\nAkademick\u00fd \u0159editel online magistersk\u00e9ho programu \u201eData Science\u201c\n<\/p><\/blockquote>\n<p>Nedostatek kari\u00e9rn\u00edho stropu je hlavn\u00ed v\u00fdhodou magistersk\u00e9ho programu. B\u011bhem dvou let z\u00edsk\u00e1 specialista silnou teoretickou z\u00e1kladnu. Takto vypad\u00e1 u\u017e prvn\u00ed semestr v programu Data Science NTNU \u201eMISI\u0160\u201c:<\/p>\n<ul>\n<li>\u00davod do Data Science. 2 t\u00fddny.<\/li>\n<li>Z\u00e1klady anal\u00fdzy dat. Zpracov\u00e1n\u00ed dat. 2 t\u00fddny<\/li>\n<li>Strojov\u00e9 u\u010den\u00ed. P\u0159edzpracov\u00e1n\u00ed dat. 2 t\u00fddny<\/li>\n<li>EDA. Pr\u016fzkumn\u00e1 anal\u00fdza dat. 3 t\u00fddny<\/li>\n<li>Hlavn\u00ed algoritmy strojov\u00e9ho u\u010den\u00ed. \u010c1 + \u010c2 (6 t\u00fddn\u016f)<\/li>\n<\/ul>\n<p>\nP\u0159itom je mo\u017en\u00e9 paraleln\u011b z\u00edsk\u00e1vat praktick\u00e9 zku\u0161enosti v pr\u00e1ci. Nic nebr\u00e1n\u00ed tomu, aby se student po ovl\u00e1dnut\u00ed pot\u0159ebn\u00fdch n\u00e1stroj\u016f uch\u00e1zel o pozici juniora. Jen\u017ee na rozd\u00edl od absolventa kurz\u016f magistr ve studiu nep\u0159est\u00e1v\u00e1 a d\u00e1le se prohlubuje v profesi. V budoucnu to umo\u017e\u0148uje bez omezen\u00ed rozv\u00edjet se v oblasti Data Science.<\/p>\n<blockquote><p>Na webov\u00fdch str\u00e1nk\u00e1ch univerzity v\u011bdy a technologi\u00ed \u201eMISIS\u201c prob\u00edhaj\u00ed <noindex><a rel=\"nofollow\" href=\"https:\/\/data.misis.ru\/?utm_source=habr&amp;utm_medium=st&amp;utm_campaign=hhmail&amp;utm_term=statiahh&amp;utm_content=2707#dayopendoor\">Dny otev\u0159en\u00fdch dve\u0159\u00ed a webin\u00e1\u0159e<\/a><\/noindex> pro ty, kte\u0159\u00ed cht\u011bj\u00ed pracovat v oblasti Data Science. Z\u00e1stupci NITU \u201eMISIS\u201c, SkillFactory, HeadHunter, Facebook, Mail.ru Group a Yandex vypr\u00e1v\u011bj\u00ed o nejd\u016fle\u017eit\u011bj\u0161\u00edch t\u00e9matech:<\/p>\n<ul>\n<li>\u201eJak naj\u00edt sv\u00e9 m\u00edsto v oblasti Data Science?\u201c,<\/li>\n<li>\u201eLze se st\u00e1t data scientistem od nuly?\u201c,<\/li>\n<li>\u201eZ\u016fstane pot\u0159eba data scientist\u016f i za 2-5 let?\u201c,<\/li>\n<li>\u201eNa jak\u00fdch \u00fakolech pracuj\u00ed specialist\u00e9 v datov\u00e9 v\u011bd\u011b?\u201c,<\/li>\n<li>\u201eJak vybudovat kari\u00e9ru v oblasti Data Science?\u201c<\/li>\n<\/ul>\n<p>\nStudium online, diplom st\u00e1tn\u00edho vzd\u011bl\u00e1n\u00ed. <noindex><a rel=\"nofollow\" href=\"https:\/\/data.misis.ru\/?utm_source=habr&amp;utm_medium=st&amp;utm_campaign=hhmail&amp;utm_term=statiahh&amp;utm_content=2707\">P\u0159ihl\u00e1\u0161ky do programu<\/a><\/noindex> se p\u0159ij\u00edmaj\u00ed do <b>10. srpna<\/b>.<\/p><\/blockquote>\n<p>Zdroj: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/513566\/\">habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u043e \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u044f\u043c HeadHunter \u0438 Mail.ru \u0441\u043f\u0440\u043e\u0441 \u043d\u0430 \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u0438\u0441\u0442\u043e\u0432 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 Data Science \u043f\u0440\u0435\u0432\u044b\u0448\u0430\u0435\u0442 \u043f\u0440\u0435\u0434\u043b\u043e\u0436\u0435\u043d\u0438\u0435, \u043d\u043e \u0434\u0430\u0436\u0435 \u0442\u0430\u043a \u043c\u043e\u043b\u043e\u0434\u044b\u043c \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u0438\u0441\u0442\u0430\u043c \u043d\u0435 \u0432\u0441\u0435\u0433\u0434\u0430 \u0443\u0434\u0430\u0435\u0442\u0441\u044f \u043d\u0430\u0439\u0442\u0438 \u0440\u0430\u0431\u043e\u0442\u0443. \u0420\u0430\u0441\u0441\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u043c, \u0447\u0435\u0433\u043e \u043d\u0435 \u0445\u0432\u0430\u0442\u0430\u0435\u0442 \u0432\u044b\u043f\u0443\u0441\u043a\u043d\u0438\u043a\u0430\u043c \u043a\u0443\u0440\u0441\u043e\u0432 \u0438 \u0433\u0434\u0435 \u0443\u0447\u0438\u0442\u044c\u0441\u044f \u0442\u0435\u043c, \u043a\u0442\u043e \u043f\u043b\u0430\u043d\u0438\u0440\u0443\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0443\u044e \u043a\u0430\u0440\u044c\u0435\u0440\u0443 \u0432 Data Science. \u00ab\u041e\u043d\u0438 \u043f\u0440\u0438\u0445\u043e\u0434\u044f\u0442 \u0438 \u0434\u0443\u043c\u0430\u044e\u0442, \u0447\u0442\u043e \u0441\u0435\u0439\u0447\u0430\u0441 \u0431\u0443\u0434\u0443\u0442 \u0437\u0430\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0442\u044c 500\u043a \u0432 \u0441\u0435\u043a\u0443\u043d\u0434\u0443, \u043f\u043e\u0442\u043e\u043c\u0443 \u0447\u0442\u043e \u0437\u043d\u0430\u044e\u0442 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-90698","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - 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