{"id":1380,"date":"2024-08-25T16:06:56","date_gmt":"2024-08-25T16:06:56","guid":{"rendered":"https:\/\/thinkeduhub.com\/?page_id=1380"},"modified":"2025-01-30T16:36:27","modified_gmt":"2025-01-30T16:36:27","slug":"ai-python","status":"publish","type":"page","link":"https:\/\/thinkeduhub.com\/hu\/ai-python\/","title":{"rendered":"ai python"},"content":{"rendered":"
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AI Python<\/h2>\n<\/div><\/div>\n\n\n\n
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Szakmai tud\u00e1s fiataloknak<\/h3>\n\n\n\n

Scoolereink betekint\u00e9st nyernek az adattudom\u00e1ny, a g\u00e9pi tanul\u00e1s, a predikt\u00edv algoritmusok \u00e9s a neur\u00e1lis h\u00e1l\u00f3zatok gyakorlati alkalmaz\u00e1sainak vil\u00e1g\u00e1ba, amelyek mesters\u00e9ges intelligenci\u00e1t ig\u00e9nyl\u0151 probl\u00e9m\u00e1k megold\u00e1s\u00e1ra szolg\u00e1lnak. <\/p>\n<\/div>\n\n\n\n

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A f\u00e9l\u00e9v v\u00e9g\u00e9re a di\u00e1kok k\u00e9pesek lesznek \u00f6n\u00e1ll\u00f3an programozni \u00e9s alkalmazni a g\u00e9pi tanul\u00e1s algoritmusait Python nyelven \u2013 k\u00fcl\u00f6nb\u00f6z\u0151 m\u00f3dszerek seg\u00edts\u00e9g\u00e9vel. Mindez megalapozza a tov\u00e1bbi adattudom\u00e1nyi ismereteket \u00e9s a r\u00e9sztvev\u0151k szakmai tanulm\u00e1nyait.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Alapvet\u0151 inform\u00e1ci\u00f3k<\/p>\n<\/div>\n\n\n\n

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Kateg\u00f3ria<\/p>\n\n\n\n

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Programoz\u00e1s<\/p>\n<\/div>\n\n\n\n

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Koroszt\u00e1ly<\/p>\n\n\n\n

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13-t\u00f3l 18 \u00e9ves korig<\/p>\n<\/div>\n\n\n\n

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Csoport<\/p>\n\n\n\n

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Legfeljebb 12 tanul\u00f3<\/p>\n<\/div>\n\n\n\n

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El\u0151felt\u00e9tel<\/p>\n\n\n\n

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Python 433 Kurs ili polo\u017een PCEP ispit<\/p>\n<\/div>\n\n\n\n

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Platform<\/p>\n\n\n\n

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MyLogiscool hozz\u00e1f\u00e9r\u00e9s 24\/7<\/p>\n<\/div>\n\n\n\n

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A kurzus id\u0151tartama<\/p>\n\n\n\n

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4,5 h\u00f3nap<\/p>\n<\/div>\n\n\n\n

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\u00d3rasz\u00e1m<\/p>\n\n\n\n

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34 \u00f3ra<\/p>\n<\/div>\n\n\n\n

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\u00d3ra hossza<\/p>\n\n\n\n

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45 perc<\/p>\n<\/div>\n\n\n\n

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Havi r\u00e9szlet<\/p>\n\n\n\n

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6.800 RSD<\/p>\n\n\n\n

(4×6.800; 1×3.400 RSD)<\/p>\n<\/div>\n\n\n\n

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\u00d3rad\u00edj<\/p>\n\n\n\n

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900 RSD<\/p>\n<\/div>\n\n\n\n

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Kedvezm\u00e9nyek<\/p>\n\n\n\n

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5% \u2013 Hozz magaddal egy bar\u00e1tot<\/p>\n\n\n\n

5% \u2013 T\u00f6bb Th!nk kurzus<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Alapvet\u0151 jellemz\u0151k<\/h2>\n\n\n\n
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A kurzus a k\u00f6vetkez\u0151 t\u00e9m\u00e1kra \u00f6sszpontos\u00edt:<\/p>\n\n\n\n

\u25b6\ufe0f Az adattudom\u00e1nyi m\u00f3dszerek gyakorlati alkalmaz\u00e1sa<\/p>\n\n\n\n

\u25b6\ufe0f CRISP-DM metodol\u00f3gia adattudom\u00e1nyi projektekhez, alulilleszt\u00e9s \u00e9s t\u00falilleszt\u00e9s kezel\u00e9se<\/p>\n\n\n\n

\u25b6\ufe0f Adatvizualiz\u00e1ci\u00f3<\/p>\n\n\n\n

\u25b6\ufe0f Fel\u00fcgyelt tanul\u00e1s: oszt\u00e1lyoz\u00e1si \u00e9s regresszi\u00f3s probl\u00e9m\u00e1k, valamint m\u00f3dszerek (kNN, d\u00f6nt\u00e9si fa, line\u00e1ris \u00e9s logisztikus regresszi\u00f3)<\/p>\n\n\n\n

\u25b6\ufe0f Fel\u00fcgyelet n\u00e9lk\u00fcli tanul\u00e1s: klaszterez\u00e9s \u00e9s m\u00f3dszerek (k-k\u00f6z\u00e9p, hierarchikus klaszterez\u00e9s, DBSCAN)<\/p>\n\n\n\n

\u25b6\ufe0f Aj\u00e1nl\u00f3rendszerek, asszoci\u00e1ci\u00f3s szab\u00e1lyok, anom\u00e1liadetekt\u00e1l\u00e1s<\/p>\n\n\n\n

\u25b6\ufe0f \u00d6n\u00e1ll\u00f3 projektfeladatok v\u00e9grehajt\u00e1sa.<\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

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Regisztr\u00e1ci\u00f3<\/h2>\n\n\n\n
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T\u00f6ltse ki az \u0171rlapot a kurzusra val\u00f3 jelentkez\u00e9shez.<\/h2>\n\n\n\n

Hamarosan felvessz\u00fck \u00d6nnel a kapcsolatot minden sz\u00fcks\u00e9ges inform\u00e1ci\u00f3val.<\/p>\n\n\n

\n Kurzus beiratkozas<\/legend>