Pehea e kūʻai aku ai ʻo Data Science iā ʻoe i ka hoʻolaha? Nīnauele me kahi ʻenekini Unity

ʻO kahi pule i hala aku nei, ua kamaʻilio ʻo Nikita Alexandrov, Data Scientist ma Unity Ads, ma kā mākou ʻoihana pūnaewele, kahi e hoʻomaikaʻi ai ʻo ia i nā algorithms hoʻololi. Noho ʻo Nikita i Finland i kēia manawa, a ma waena o nā mea ʻē aʻe, ua ʻōlelo ʻo ia e pili ana i ke ola IT ma ka ʻāina.

Kaʻana like mākou me ʻoe i ka transcript a me ka hoʻopaʻa ʻana o ka nīnauele.

ʻO Nikita Aleksandrov koʻu inoa, ua ulu au ma Tatarstan a ua puka au mai ke kula ma laila, a ua komo au i nā olympiads matematika. Ma hope o kēlā, ua komo ʻo ia i ke Kumu o ka ʻEpekema ʻEpekema ma ke Kula Kiʻekiʻe o ka ʻEpekema a hoʻopau i kāna kēkelē laepua ma laila. I ka hoʻomaka ʻana o koʻu makahiki 4 ua hele au i kahi haʻawina hoʻololi a hoʻohana i hoʻokahi kau ma Finland. Ua makemake au ma laila, ua komo au i ka papahana haku ma ke Kulanui ʻo Aalto, ʻoiai ʻaʻole au i hoʻopau piha - ua hoʻopau au i nā papa a pau a hoʻomaka wau e kākau i kaʻu thesis, akā ua haʻalele wau e hana ma Unity me ka loaʻa ʻole o koʻu kēkelē. I kēia manawa ke hana nei au ma Unity data scientist, kapa ʻia ke keʻena ʻo Operate Solutions (ua kapa ʻia ʻo Monetization ma mua); Hāʻawi pololei kaʻu hui i ka hoʻolaha. ʻO ia hoʻi, ka hoʻolaha pāʻani - ka mea i ʻike ʻia i ka wā e pāʻani ai ʻoe i kahi pāʻani kelepona a pono e loaʻa ke ola hou, no ka laʻana. Ke hana nei au i ka hoʻomaikaʻi ʻana i ka hoʻololi hoʻolaha - ʻo ia hoʻi, e hoʻonui i ka mea pāʻani e kaomi i ka hoʻolaha.

Pehea ʻoe i neʻe ai?

ʻO ka mea mua, ua hele mai au i Finland e aʻo no kahi kau hoʻololi, a laila hoʻi au i Rusia a hoʻopau i kaʻu diploma. A laila ua komo au i ka papahana haku ma ke Kulanui ʻo Aalto ma ke aʻo ʻana i nā mīkini / ʻepekema data. No ka mea he haumana ho'ololi au, 'a'ole pono au e lawe i ka ho'okolokolo 'ōlelo Pelekānia; Ua maʻalahi wau, ʻike wau i kaʻu e hana nei. Ua noho au ma ʻaneʻi no 3 makahiki i kēia manawa.

Pono anei ʻo Finnish?

Pono inā e aʻo ʻoe ma ʻaneʻi no ke kēkelē laepua. He liʻiliʻi loa nā papahana ma ka ʻōlelo Pelekania no nā bachelors; pono ʻoe i ka Finnish a i ʻole Suedena - ʻo ia ka lua o ka ʻōlelo mokuʻāina, aʻo kekahi mau kulanui ma Suedena. Akā ma nā papahana haku a me PhD, aia ka hapa nui o nā papahana ma ka ʻōlelo Pelekania. Inā mākou e kamaʻilio e pili ana i ka kamaʻilio ʻana i kēlā me kēia lā a me ke ola o kēlā me kēia lā, ʻōlelo ka hapa nui o ka poʻe ma ʻaneʻi i ka ʻōlelo Pelekane, ma kahi o 90%. Noho maʻamau ka poʻe no nā makahiki i ka manawa (ke ola nei koʻu hoa hana no 20 mau makahiki) me ka ʻole o ka ʻōlelo Finnish.

ʻOiaʻiʻo, inā makemake ʻoe e noho ma ʻaneʻi, pono ʻoe e hoʻomaopopo i ka Finnish ma ke kiʻekiʻe o ka hoʻopiha ʻana i nā palapala - inoa hope, inoa mua, a pēlā aku.

He ʻokoʻa ka maikaʻi o ka hoʻonaʻauao mai nā kulanui ma ka Russian Federation? Hāʻawi lākou i nā kumu kūpono a pau no kahi mea ʻōpio?

Heʻokoʻa ka maikaʻi. Me he mea lā iaʻu ma Rusia e hoʻāʻo nei lākou e aʻo i nā mea he nui i ka manawa hoʻokahi: nā hoʻohālikelike ʻokoʻa, ka makemakika discrete a me nā mea hou aku. ʻO ka ʻoiaʻiʻo, pono ʻoe e lawe i nā mea hou aku, ma ke ʻano he papa a i ʻole dissertation, e aʻo i kahi mea hou iā ʻoe iho, e lawe i kekahi mau papa. Eia ua maʻalahi iaʻu i ka papahana haku; Ua ʻike nui au i nā mea e hana nei. Eia hou, ma Finland kahi bachelor ʻaʻole ia he loea; aia nō kahi mahele. I kēia manawa, inā loaʻa iā ʻoe kahi kekelē master, a laila hiki iā ʻoe ke loaʻa kahi hana. Au e olelo aku i loko o ka haku papahana ma Finland ka mea nui nā mākau kaiapili, he mea nui e komo, e hana; aia nā papahana noiʻi. Inā he noiʻi hoihoi iā ʻoe, a makemake ʻoe e ʻeli hohonu, a laila hiki iā ʻoe ke kiʻi i nā pilina o ke kumu, hana i kēia kuhikuhi, a hoʻomohala.

ʻO ia hoʻi, ʻo ka pane he "ʻae," akā pono ʻoe e hana i ka pilikanaka, pili i nā manawa āpau inā loaʻa. Ua hele kekahi o koʻu mau hoaaloha e hana ma kahi hoʻomaka ma ke awāwa - aia kahi papahana ma ke kulanui e ʻimi ana i nā hoʻomaka kūpono a hoʻonohonoho i nā nīnauele. Manaʻo wau ua hele ʻo ia i CERN ma hope.

Pehea e hoʻoikaika ai kahi hui ma Finland i nā limahana, he aha nā pōmaikaʻi?

Ma waho aʻe o ka maopopo (uku), aia nā pōmaikaʻi kaiaulu. Eia kekahi laʻana, ka nui o ka haʻalele makuahine no nā mākua. Aia nā 'inikua olakino, nā waihona, nā koho. Loaʻa ka loaʻa ʻole o nā lā hoʻomaha. ʻAʻohe mea kūikawā, ma ke kumu.

He sauna ko mākou keʻena, no ka laʻana.

Aia kekahi mau coupons - kahi kālā no ka ʻaina awakea, no ka halihali lehulehu, no nā hanana moʻomeheu a me nā haʻuki (nā hale hōʻikeʻike, nā haʻuki).

He aha ka mea a ka haumāna humanities e ʻōlelo ai no ke komo ʻana i IT?

E hana hou i ka papa kula a komo i ka HSE? Loaʻa pinepine ka poʻe programmer i ka makemakika/Olympiads...

Aʻo wau, ʻoiaʻiʻo, e hoʻomaikaʻi i kāu makemakika. Akā ʻaʻole pono e hana hou i ka papa kula. ʻOi aku ka pololei, pono e hana hou ʻia inā ʻaʻole ʻoe e hoʻomanaʻo i kekahi mea. Eia hou, pono ʻoe e hoʻoholo i ka IT āu e makemake ai e komo. No ka lilo ʻana i mea hoʻomohala mua, ʻaʻole pono ʻoe e ʻike i ka makemakika: pono ʻoe e lawe i nā papa mua a aʻo. Ua hoʻoholo koke koʻu hoaaloha e kākau inoa i nā papa mai Accenture, ke aʻo nei ʻo ia iā Scala; ʻAʻole ʻo ia he kanaka kanaka, akā ʻaʻohe ona ʻike polokalamu. Ma muli o ka mea āu e makemake ai e hoʻolālā a me ka mea, pono ʻoe i ka nui o ka makemakika. ʻO kaʻoiaʻiʻo, pono ka mīkini aʻo kūikawā i ka makemakika, ma kekahi ala a i ʻole. Akā, inā makemake ʻoe e hoʻāʻo, nui nā kumu aʻo like ʻole, wehe ʻike, nā wahi e hiki ai iā ʻoe ke pāʻani me kahi neural network a kūkulu paha iā ʻoe iho, a i ʻole e kiʻi i kahi mea i mākaukau, hoʻololi i nā ʻāpana a ʻike i ke ʻano o ka loli. Aia nā mea a pau i ka ikaika o ka hoʻoikaika.

Inā ʻaʻole ia he mea huna - uku, ʻike, he aha kāu e kākau ai?

Kākau wau ma Python - he ʻōlelo holoʻokoʻa no ke aʻo ʻana i ka mīkini a me ka ʻepekema data. ʻIke - loaʻa nā ʻike like ʻole; He ʻenekini maʻalahi wau i kekahi mau ʻoihana, aia wau ma kahi internship no kekahi mau mahina ma Moscow. ʻAʻohe hana manawa piha ma mua o Unity. Hele mai au i laila ma ke ʻano he intern, hana ma ke ʻano he intern no 9 mahina, a laila hoʻomaha, a i kēia manawa ua hana au no hoʻokahi makahiki. He hoʻokūkū ka uku, ma luna o ka waena waena. E loaʻa i kahi loea hoʻomaka mai 3500 EUR; He ʻokoʻa kēia mai kahi ʻoihana a ʻoihana. Ma ka laulā, ʻo 3.5-4 kahi uku hoʻomaka.

He aha nā puke a me nā haʻawina āu e paipai ai?

ʻAʻole au makemake nui e aʻo mai nā puke - he mea nui iaʻu e hoʻāʻo ma ka lele; hoʻoiho i kahi mea i mākaukau a hoʻāʻo iā ʻoe iho. Manaʻo wau iaʻu iho he mea hoʻokolohua, no laila ʻaʻole hiki iaʻu ke kōkua i nā puke. Akā ua nānā au i kekahi mau nīnauele a me nā hoʻolaha ola ma ʻaneʻi, kahi e kamaʻilio kikoʻī ai ka mea haʻiʻōlelo ʻelua e pili ana i nā puke.

Aia nā kumu aʻo like ʻole. Inā makemake ʻoe e hoʻāʻo i kahi algorithm, e lawe i ka inoa o ka algorithm, ke ʻano, nā papa hana, a komo i loko o ka ʻimi. ʻO ka mea i puka mai ma ke ʻano he loulou mua, a laila e nānā.

Pehea ka lōʻihi o ka noho maʻemaʻe?

Ma hope o ka ʻauhau - pono ʻoe e lawe i nā ʻauhau me 8% (ʻaʻole ia he ʻauhau, akā he ʻauhau) - 2/3 o ka uku. ʻOi aku ka ikaika o ka uku - ʻoi aku ka nui o kāu loaʻa, ʻoi aku ka kiʻekiʻe o ka ʻauhau.

ʻO wai nā hui e noi ana no ka hoʻolaha?

Pono ʻoe e hoʻomaopopo i ke komo ʻana o Unity / Unity Ads i nā pāʻani kelepona hoʻolaha. ʻO ia hoʻi, loaʻa iā mākou kahi niche, ʻike maikaʻi mākou i nā pāʻani kelepona, hiki iā ʻoe ke hana iā lākou ma Unity. Ke kākau ʻoe i kahi pāʻani, makemake ʻoe e loaʻa kālā mai ia mea, a ʻo ka monetization kekahi ala.
Hiki i kēlā me kēia hui ke noi no ka hoʻolaha - nā hale kūʻai pūnaewele, nā noi kālā like ʻole. Pono nā kānaka a pau i ka hoʻolaha. ʻO ka mea kikoʻī, ʻo kā mākou mea kūʻai nui nā mea hoʻomohala pāʻani paʻani.

He aha nā papahana maikaʻi e hana ai e hoʻomaikaʻi i kou mau akamai?

He nīnau maikaʻi. Inā mākou e kamaʻilio e pili ana i ka ʻepekema data, pono ʻoe e hoʻomaikaʻi iā ʻoe iho ma o kahi papa pūnaewele (no ka laʻana, aia ʻo Stanford) a i ʻole ke kulanui pūnaewele. Aia nā kahua like ʻole āu e uku ai - no ka laʻana, Udacity. Aia nā haʻawina home, nā wikiō, ke aʻo ʻana, akā ʻaʻole maʻalahi ka leʻaleʻa.

ʻOi aku ka liʻiliʻi o kāu mau makemake (e like me ke ʻano o ka hoʻoikaika ʻana i ke aʻo ʻana), ʻoi aku ka paʻakikī o ka loaʻa ʻana o nā papahana. Hiki iā ʻoe ke hoʻāʻo e komo i nā hoʻokūkū kaggle: e hele i kaggle.com, nui nā hoʻokūkū aʻo mīkini like ʻole ma laila. Lawe ʻoe i kahi mea i loaʻa i kekahi ʻano baseline i pili iā ia; hoʻoiho a hoʻomaka e hana. ʻO ia, he nui nā ala: hiki iā ʻoe ke aʻo iā ʻoe iho, hiki iā ʻoe ke lawe i kahi papa pūnaewele - manuahi a uku ʻole paha, hiki iā ʻoe ke komo i nā hoʻokūkū. Inā makemake ʻoe e ʻimi i kahi hana ma Facebook, Google, a pēlā aku, pono ʻoe e aʻo pehea e hoʻoponopono ai i nā pilikia algorithmic - ʻo ia hoʻi, pono ʻoe e hele i LeetCode, e kiʻi i kāu mau mākau ma laila i mea e hele ai i nā nīnauele.

E wehewehe i kahi palapala ala pōkole no ke aʻo ʻana i ka mīkini?

E haʻi aku wau iā ʻoe ma ke ʻano kūpono, me ka ʻole o ka hoʻokalakupua. Lawe mua ʻoe i nā papa makemakika ma uni, pono ʻoe i ka ʻike a me ka ʻike o ka algebra linear, probability and statistics. Ma hope o kēlā, haʻi kekahi iā ʻoe e pili ana iā ML; inā noho ʻoe ma ke kūlanakauhale nui, pono e loaʻa nā kula e hāʻawi ana i nā papa ML. ʻO ka mea kaulana loa ʻo SHAD, Yandex School of Data Analysis. Inā hele ʻoe a hiki iā ʻoe ke aʻo no ʻelua makahiki, e loaʻa iā ʻoe ka waihona ML holoʻokoʻa. Pono ʻoe e hoʻomaikaʻi hou i kāu mau akamai i ka noiʻi a me ka hana.

Inā he mau koho ʻē aʻe: no ka laʻana, loaʻa ʻo Tinkov i nā papa ma ke aʻo ʻana i ka mīkini me ka manawa e loaʻa ai kahi hana ma Tinkoff ma hope o ka puka ʻana. Inā kūpono kēia iā ʻoe, e kākau inoa no kēia mau papa. Aia nā paepae komo ʻokoʻa: no ka laʻana, loaʻa iā ShAD nā hoʻokolohua komo.
Inā ʻaʻole ʻoe makemake e lawe i nā papa maʻamau, hiki iā ʻoe ke hoʻomaka me nā papa pūnaewele, ʻoi aku ka nui o ia mau papa. Aia ia iā ʻoe; inā he ʻōlelo Pelekania maikaʻi kāu, maikaʻi, maʻalahi ke loaʻa. Inā ʻaʻole, a laila aia kekahi mea ma laila. Loaʻa i ka lehulehu nā haʻiʻōlelo ShAD like.
Ma hope o ka loaʻa ʻana o kahi kumu kumu, hiki iā ʻoe ke neʻe i mua - no nā internships, noiʻi, a pēlā aku.

Hiki paha ke aʻo iā ʻoe iho i ka aʻo mīkini? Ua hālāwai anei ʻoe me kahi mea polokalamu polokalamu?

Manaʻo wau ʻae. Pono wale ʻoe e hoʻoikaika ikaika. Hiki i kekahi ke aʻo i ka ʻōlelo Pelekania ma kāna iho, no ka laʻana, akā pono kekahi e lawe i nā papa, a ʻo ia wale nō ke ala e aʻo ai kēia kanaka. Ua like ia me ML. ʻOiai ʻaʻole wau i ʻike i kahi mea papahana nāna i aʻo i nā mea a pau ma kāna iho, ʻaʻole paha he nui kaʻu mau hoaaloha; Ua aʻo wale koʻu mau hoaaloha ma ke ʻano maʻamau. ʻAʻole wau i manaʻo e ʻōlelo pono ʻoe e aʻo 100% i kēia ala: ʻo ka mea nui kāu makemake, kou manawa. ʻOiaʻiʻo, inā ʻaʻohe kumu makemakika, pono ʻoe e hoʻolilo i ka manawa nui e hoʻomohala ai.
Ma waho aʻe o ka hoʻomaopopo ʻana i ke ʻano o ka ʻepekema data: ʻAʻole wau e hana i ka ʻikepili data iaʻu iho.
e like me ka noiʻi. ʻAʻole kā mākou ʻoihana he hale hana kahi e hoʻomohala ai mākou i nā ʻano hana i ka wā e hoʻopaʻa ana iā mākou iho i loko o ka hale hana no ʻeono mahina. Hana pololei wau me ka hana ʻana, a pono wau i nā mākau ʻenekinia; Pono wau e kākau code a loaʻa nā mākau ʻenekinia e hoʻomaopopo i ka hana. Haʻalele pinepine ka poʻe i kēia mau hiʻohiʻona ke kamaʻilio e pili ana i ka ʻepekema data. Nui nā moʻolelo o ka poʻe me nā PhD e kākau ana i hiki ʻole ke heluhelu ʻia, weliweli, unstructured code a loaʻa nā pilikia nui ma hope o ko lākou hoʻoholo ʻana e hele i ka ʻoihana. ʻO ia hoʻi, i ka hui pū ʻana me Machine Learning, ʻaʻole pono e poina kekahi e pili ana i nā mākau ʻenehana.

ʻO ka ʻepekema ʻikepili kahi kūlana ʻaʻole ʻōlelo e pili ana iā ia iho. Hiki iā ʻoe ke loaʻa kahi hana ma kahi ʻoihana e pili ana i ka ʻepekema data, a e kākau ʻoe i nā nīnau SQL, a i ʻole e loaʻa ka loiloi logistic maʻalahi. Ma ke kumu, ʻo ia hoʻi ke aʻo ʻana i ka mīkini, akā aia kēlā me kēia hui i kona ʻike ponoʻī i ke ʻano o ka ʻepekema data. No ka laʻana, ʻōlelo kaʻu hoaaloha ma Facebook ʻo ka ʻepekema data ke holo wale nā ​​​​kānaka i nā hoʻokolohua helu: kaomi i nā pihi, e hōʻiliʻili i nā hopena a hōʻike iā lākou. Ma ka manawa like, hoʻomaikaʻi wau iho i nā ʻano hoʻololi a me nā algorithm; i kekahi mau ʻoihana ʻē aʻe paha e kapa ʻia kēia ʻano loea aʻo mīkini. Hiki ke ʻokoʻa nā mea i nā ʻoihana like ʻole.

He aha nā hale waihona puke āu e hoʻohana ai?

Hoʻohana mākou iā Keras a me TensorFlow. Hiki nō hoʻi ʻo PyTorch - ʻaʻole koʻikoʻi kēia, hiki iā ʻoe ke hana i nā mea like a pau - akā i kekahi manawa ua hoʻoholo ʻia e hoʻohana iā lākou. Me ka hana e kū nei he paʻakikī ke hoʻololi.

ʻAʻole ʻo Unity wale nō ka poʻe ʻepekema ʻikepili e hoʻomaikaʻi i ka algorithm huli ʻana, akā ʻo GameTune kekahi mea e hoʻomaikaʻi ai ʻoe i nā metric e pili ana i ka loaʻa kālā a i ʻole ka paʻa ʻana me ka hoʻohana ʻana i nā aʻo like ʻole. E ʻōlelo kākou ua pāʻani kekahi i ka pāʻani a ʻōlelo mai: ʻAʻole maopopo iaʻu, ʻaʻole oʻu hoihoi - haʻalele ʻo ia; He mea maʻalahi loa ia no kekahi, akā naʻe, hāʻawi pū ʻo ia. ʻO ia ke kumu e pono ai ʻo GameTune - kahi hana e hoʻohālikelike i ka paʻakikī o nā pāʻani e pili ana i ka hiki o ka mea pāʻani, a i ʻole ka mōʻaukala pāʻani, a i ʻole ke kūʻai pinepine ʻana i kekahi mea i-app.

Aia pū kekahi Unity Labs - hiki iā ʻoe ke google pū kekahi. Aia kahi wikiō kahi e lawe ai ʻoe i kahi pahu cereal, a ma ke kua o ia mea he mau pāʻani e like me nā mazes - akā kūpono lākou me ka mea i hoʻonui ʻia, a hiki iā ʻoe ke hoʻomalu i ke kanaka ma ka pahu pahu. Nani loa.

Hiki iā ʻoe ke kamaʻilio pololei e pili ana i Unity Ads. Inā hoʻoholo ʻoe e kākau i kahi pāʻani, a hoʻoholo e hoʻolaha a loaʻa kālā, pono ʻoe e hoʻoponopono i kekahi mau pilikia paʻakikī.

E hoʻomaka wau me kahi laʻana: Ua hoʻolaha ʻo Apple i ka hoʻomaka ʻana o iOS 14. I loko o ia mea, hiki i kahi mea pāʻani ke komo i loko o ka noi a ʻōlelo ʻaʻole makemake ʻo ia e kaʻana like i kāna Device-ID me kekahi. Eia naʻe, ʻae ʻo ia e hoʻohaʻahaʻa ka maikaʻi o ka hoʻolaha. Akā i ka manawa like, he paʻakikī iā mākou no ka mea inā ʻaʻole hiki iā mākou ke ʻike iā ʻoe, a laila ʻaʻole hiki iā mākou ke hōʻiliʻili i kekahi mau ana, a e liʻiliʻi ka ʻike e pili ana iā ʻoe. He mea paʻakikī loa i ka ʻepekema ʻikepili e hoʻopaʻa pono i ka hana ma kahi honua i ʻoi aku ka paʻa i ka pilikino a me ka pale ʻikepili - aia ka liʻiliʻi a me ka liʻiliʻi o ka ʻikepili, a me nā ʻano i loaʻa.

Ma kahi o Unity, aia nā kanaka nunui e like me Facebook a me Google - a, me he mea lā, no ke aha mākou e pono ai i Unity Ads? Akā pono ʻoe e hoʻomaopopo he ʻokoʻa paha ka hana o kēia mau pūnaewele hoʻolaha ma nā ʻāina like ʻole. Ma ka ʻōlelo pili, aia nā ʻāina Tier 1 (ʻAmelika, Kanada, Australia); Aia nā ʻāina ʻo Tier 2 (Asia), aia nā ʻāina ʻo Tier 2 (India, Brazil). Hiki i nā pūnaewele hoʻolaha ke hana ʻokoʻa i loko o lākou. ʻO ke ʻano o ka hoʻolaha ʻana i hoʻohana ʻia kekahi mea nui. ʻO ia ke ʻano maʻamau, a i ʻole ka hoʻolaha "uku" - i ka manawa, no ka laʻana, i mea e hoʻomau ai mai ka wahi like ma hope o ka pāʻani, pono ʻoe e nānā i kahi hoʻolaha. Nā ʻano hoʻolaha like ʻole, nā kānaka like ʻole. Ma kekahi mau ʻāina, ʻoi aku ka maikaʻi o ka ʻoihana hoʻolaha hoʻokahi, ma nā ʻāina ʻē aʻe. A ma ke ʻano he memo hou aʻe, ua lohe au ua ʻoi aku ka paʻakikī o ka hoʻohui ʻana o Google AdMob ma mua o Unity.

ʻO ia hoʻi, inā ʻoe i hana i kahi pāʻani ma Unity, a laila hoʻohui ʻia ʻoe i loko o Unity Ads. ʻO kaʻokoʻa ka maʻalahi o ka hoʻohui. He aha kaʻu e ʻōlelo aku ai: aia kekahi mea e like me ka mediation; loaʻa nā kūlana like ʻole: hiki iā ʻoe ke hoʻonohonoho i nā kūlana i ka "wailele" no nā hoʻolaha hoʻolaha. Hiki iā ʻoe ke ʻōlelo, no ka laʻana, penei: Makemake au e hōʻike mua ʻia ʻo Facebook, a laila Google, a laila Unity. A, inā hoʻoholo ʻo Facebook a me Google ʻaʻole e hōʻike i nā hoʻolaha, a laila e hana ʻo Unity. ʻOi aku ka nui o nā pūnaewele hoʻolaha i loaʻa iā ʻoe, ʻoi aku ka maikaʻi. Hiki ke noʻonoʻo ʻia he hoʻopukapuka kālā, akā ke hoʻolilo nei ʻoe i kahi helu ʻokoʻa o nā pūnaewele hoʻolaha i ka manawa hoʻokahi.
Hiki iā ʻoe ke kamaʻilio e pili ana i nā mea nui no ka holomua o kahi hoʻolaha hoʻolaha. ʻOiaʻiʻo, ʻaʻohe mea kūikawā ma aneʻi: pono ʻoe e hōʻoia i ka pili ʻana o ka hoʻolaha i ka ʻike o kāu noi. Hiki iā ʻoe, no ka laʻana, e ʻimi iā YouTube no ka "app ads mafia" a ʻike i ke ʻano o ka hoʻolaha ʻole ʻana i ka ʻike. Aia kekahi polokalamu i kapa ʻia ʻo Homescapes (a i ʻole Gardenscapes?). He mea nui paha inā hoʻonohonoho pono ʻia ka hoʻolaha: no laila e hōʻike ʻia ka hoʻolaha ʻana ma ka ʻōlelo Pelekania i kahi anaina ʻōlelo Pelekania, a ma ka ʻōlelo Lūkini i kahi anaina ʻōlelo Lūkini. Loaʻa pinepine nā hewa i kēia: ʻaʻole maopopo ka poʻe iā ia, hoʻokomo lākou iā ia ma ke ʻano.
Pono ʻoe e hana i nā wikiō ʻoluʻolu like ʻole, e noʻonoʻo e pili ana i ke ʻano, e noʻonoʻo e pili ana i ka manawa e hoʻonui ai iā lākou. Ma nā hui nui, hana nā poʻe kūikawā i kēia - nā mana hoʻohana hoʻohana. Inā he mea hoʻomohala hoʻokahi ʻoe, a laila ʻaʻole pono ʻoe i kēia, a i ʻole pono ʻoe ma hope o ka loaʻa ʻana o kahi ulu.

He aha kāu mau hoʻolālā e hiki mai ana?

Ke hana mau nei au ma koʻu wahi i kēia manawa. Malia paha e loaʻa iaʻu ke kamaʻāina Finnish - hiki kēia ma hope o 5 mau makahiki o ka noho ʻana (inā ʻoi aku ka liʻiliʻi o 30 mau makahiki, pono ʻoe e lawelawe, inā ʻaʻole i hana ke kanaka i kēia ma ka ʻāina ʻē).

No ke aha ʻoe i neʻe ai i Finland?

ʻAe, ʻaʻole kēia he ʻāina kaulana loa no kahi loea IT e neʻe ai. He nui ka poʻe e neʻe me nā ʻohana no ka mea he mau pōmaikaʻi pilikanaka maikaʻi ma ʻaneʻi - nā kula kindergarten, nurseries, a me ka haʻalele makuahine no kēlā me kēia makua. No ke aha wau i neʻe ai iaʻu iho? Hiki paha iaʻu ke makemake i kēlā me kēia wahi, akā kokoke loa ʻo Finland i ka noʻonoʻo moʻomeheu; Aia nā ʻokoʻa me Rusia, ʻoiaʻiʻo, akā aia kekahi mau mea like. He liʻiliʻi ʻo ia, palekana, ʻaʻole loa e komo i nā pilikia nui. ʻAʻole kēia heʻAmelika maʻamau, kahi e hiki ai iāʻoe ke loaʻa kahi pelekikena i makemakeʻoleʻia, a e hoʻomaka kekahi mea no kēia; ʻaʻole ʻo Beretania Nui, ka mea i makemake koke e haʻalele i ka EU, a aia pū kekahi pilikia. He 5 miliona kanaka wale no maanei. ʻOiai me ka maʻi maʻi coronavirus, ua hoʻohālikelike maikaʻi ʻo Finland i nā ʻāina ʻē aʻe.

Ke hoʻolālā nei ʻoe e hoʻi i Rusia?

ʻAʻole au e hele ana. ʻAʻohe mea e pale iaʻu mai ka hana ʻana i kēia, akā ʻoluʻolu wau ma ʻaneʻi. Eia kekahi, inā wau e hana ma Rūsia, pono wau e hoʻopaʻa inoa me ka pūʻali koa, a hiki ke hoʻopaʻa ʻia au.

E pili ana i nā papahana haku ma Finland

ʻAʻohe mea kūikawā. Inā mākou e kamaʻilio e pili ana i ka ʻike o nā haʻiʻōlelo, he hoʻonohonoho paheʻe wale nō ia; aia nā mea manaʻo, kahi seminar me ka hoʻomaʻamaʻa, kahi e hoʻomaikaʻi ʻia ai kēia kumumanaʻo, a laila kahi hoʻokolokolo ma kēia mau mea āpau (ka manaʻo a me nā hana).

Hōʻike: ʻaʻole lākou e kipaku ʻia mai ka papahana o ka haku. Inā ʻaʻole ʻoe e hele i ka hōʻike, pono ʻoe e lawe i kēia papa i ke kau e hiki mai ana. He palena wale nō ka manawa o ke aʻo ʻana: no ke kēkelē laepua - ʻaʻole ʻoi aku ma mua o 7 mau makahiki, no ke kēkelē haku - 4 mau makahiki. Hiki iā ʻoe ke hoʻopau maʻalahi i nā mea a pau i loko o ʻelua makahiki, koe wale no ka papa hoʻokahi, a hoʻolōʻihi iā ia ma luna o 2 mau makahiki, a i ʻole e lawe i nā papa haʻawina.

He ʻokoʻa loa ka hana ma Moscow a ma Finland?

ʻAʻole wau e ʻōlelo. ʻO nā hui IT like, nā hana like. Ma ka moʻomeheu a me nā ʻōlelo o kēlā me kēia lā, kūpono ia, kokoke ka hana, liʻiliʻi ke kūlanakauhale. ʻO ka hale kūʻai he hoʻokahi minuke mai iaʻu, ʻekolu ka hale haʻuki, iwakāluakūmālima ka hana, puka i kēlā puka. Makemake au i nā nui; ʻAʻole au i noho i loko o nā kūlanakauhale ʻoluʻolu ma mua, aia nā mea āpau. ʻO ke ʻano nani, kokoke ke kahakai.

Akā ma ke ʻano o ka hana, manaʻo wau ua like nā mea āpau, hoʻohui a i ʻole. E pili ana i ka mākeke hana IT ma Finland, e pili ana i ke aʻo ʻana i ka mīkini, e hoʻomaopopo kekahi no nā loea e pili ana i ka ML, koi ʻia kahi PhD a i ʻole ka liʻiliʻi o ke kēkelē master. Manaʻo wau e loli kēia i ka wā e hiki mai ana. Aia nō ka manaʻo ʻino ma ʻaneʻi: inā loaʻa iā ʻoe kahi kēkelē laepua, a laila ʻaʻole hiki iā ʻoe ke lilo i loea i hoʻomaʻamaʻa ʻia, akā inā loaʻa iā ʻoe ke kēkelē master, loaʻa iā ʻoe kahi loea a hiki iā ʻoe ke hana. A inā loaʻa iā ʻoe kahi PhD, a laila ʻoluʻolu loa nā mea āpau, a hiki iā ʻoe ke hana i ka noiʻi IT. ʻOiai, me he mea lā iaʻu, ʻo ka poʻe i hoʻopau i kā lākou PhD ʻaʻole hiki ke hoʻopili piha ʻia i loko o ka ʻoihana, a ʻaʻole maopopo paha ʻo ka ʻoihana ʻaʻole wale nā ​​algorithm a me nā ʻano, akā ʻoihana pū kekahi. Inā ʻaʻole ʻoe maopopo i ka ʻoihana, a laila ʻaʻole maopopo iaʻu pehea ʻoe e ulu ai i kahi hui a hoʻomaopopo i ka hana ʻana o kēia ʻōnaehana meta holoʻokoʻa.

No laila paʻakikī loa ka manaʻo o ka neʻe ʻana i ke kula puka a loaʻa koke kahi hana; inā neʻe ʻoe i Finland me ke kēkelē laepua, he inoa ʻole ʻoe. Pono ʻoe e loaʻa kahi ʻike hana e ʻōlelo ai: Ua hana wau ma Yandex, Mail, Kaspersky Lab, etc.

Pehea e noho ai ma 500 EUR ma Finland?

Hiki iā ʻoe ke ola. Inā he haumāna ʻoe, pono ʻoe e hoʻomaopopo ʻaʻole e loaʻa iā ʻoe kahi haʻawina; Hiki i ka EU ke hāʻawi kālā, akā no nā haumāna hoʻololi wale nō. Inā ʻoe e komo ana i ke kulanui ma Finland, a laila pono ʻoe e hoʻomaopopo pehea e ola ai. Nui nā koho; inā ʻoe e hoʻopaʻa inoa i kahi papahana haku me kahi track PhD (ʻo ia hoʻi, i ka manawa like i ka papahana haku a me ka PhD), a laila mai ka makahiki mua e hana ʻoe i ka hana noiʻi a loaʻa kālā no ia.
Liʻiliʻi, akā lawa ia no ka haumāna. ʻO ka lua o ka koho he hana hapa manawa; no ka laʻana, he kōkua aʻo wau no kekahi papa a loaʻa iā 400 EUR i kēlā me kēia mahina.

Ma ke ala, loaʻa iā Finland nā pōmaikaʻi haumāna maikaʻi. Hiki iā ʻoe ke neʻe i loko o kahi dorm no 300 a i ʻole 200 EUR no ke keʻena, hiki iā ʻoe ke ʻai i nā canteens haumāna me ke kumukūʻai paʻa (ʻo nā mea āpau āu e kau ai ma kāu pā he 2.60 EUR). Ho'āʻo kekahi e ʻai i ka ʻaina kakahiaka, ka ʻaina awakea a me ka ʻaina ahiahi ma ka lumi ʻaina no 2.60; inā ʻoe e hana i kēia, hiki iā ʻoe ke ola ma 500 EUR. Akā ʻo kēia ka liʻiliʻi loa.

Ma hea ʻoe e hele ai inā makemake ʻoe e lilo i mea polokalamu?

Hiki iā ʻoe ke kākau inoa i ka Faculty of Computer Science ma ke Higher School of Economics, Moscow Institute of Physics and Technology - FIVT a me FUPM, a i ʻole ka Computer Science and Computing Committee o Moscow State University, no ka laʻana. Hiki iā ʻoe ke loaʻa kekahi mea ma St. Petersburg. Akā ʻaʻole maopopo iaʻu i ke kūlana pololei me ka aʻo ʻana i ka mīkini, e hoʻāʻo i ka googling i kēia kumuhana.

Makemake wau e ʻōlelo i ka lilo ʻana i mea papahana, ʻaʻole lawa ka hoʻomaʻamaʻa wale ʻana. He mea nui e lilo i kanaka pilikanaka, ʻoluʻolu ke kamaʻilio pū, i mea e hoʻopili koke ai. Hiki i nā pilina ke hoʻoholo. ʻO nā ʻōlelo aʻoaʻo pilikino i kahi ʻoihana e hāʻawi i kahi pono kūpono ma mua o nā mea noi ʻē aʻe; hiki iā ʻoe ke hoʻokuʻu wale i ka nānā ʻana o ka recruiter.

ʻO ka mea maʻamau, ʻaʻole maikaʻi loa ke ola ma Finland - ua neʻe au, a lilo koke nā mea āpau. Loaʻa i kēlā me kēia malihini ka haʻalulu moʻomeheu. He ʻokoʻa ko nā ʻāina like ʻole, ʻokoʻa ka noʻonoʻo, ʻokoʻa nā kānāwai. Eia kekahi laʻana, ponoʻoe e mālama i nāʻauhau iāʻoe iho - e hoʻopiha i ka kālekaʻauhau iāʻoe iho; kūʻai kaʻa, hoʻolimalima hale—he nui nā mea e hana ʻokoʻa. Paʻakikī loa inā hoʻoholo ʻoe e neʻe. ʻAʻole pili ka poʻe ma ʻaneʻi, ua like ka wā ma St. Petersburg - i Nowemapa-Dekemapa hiki ke loaʻa nā lā lā 1-2. Ke kaumaha nei kekahi ma ʻaneʻi; hele mai lākou me ka hilinaʻi e pono loa lākou ma ʻaneʻi, akā ʻaʻole kēia ka hihia, a pono lākou e loaʻa kālā ma ka pāʻani ʻana i nā lula o kekahi. He pilikia mau. Loaʻa ka manawa e hoʻi ai ʻoe no ka mea ʻaʻole ʻoe e komo.

He aha nā ʻōlelo aʻoaʻo āu e hāʻawi ai i nā mea hoʻolālā makemake?

Ke aʻo aku nei au iā ʻoe e hoʻāʻo e like me ka mea hiki, e hoʻomaopopo i ka mea āu e makemake ai. E ho'āʻo ʻaʻole e paʻa i kahi wahi: e hoʻāʻo i ka hoʻomohala Android, frontend/backend, Java, Javascript, ML, a me nā mea ʻē aʻe. A, e like me kaʻu i ʻōlelo ai, pono ʻoe e hana, e hoʻopili, e hoihoi i nā mea e hana nei; he aha nā hoaaloha, nā hoahana, nā hoaaloha e hana nei. E hele i nā papa hana, nā seminar, nā haʻi'ōlelo, e hālāwai me nā kānaka. ʻOi aku ka nui o kāu mau pilina, ʻoi aku ka maʻalahi o ka hoʻomaopopo ʻana i nā mea hoihoi e hana nei.

Ma hea kahi i hoʻohana ʻia ai ʻo Unity ma waho o nā pāʻani?

Ke hoʻāʻo nei ʻo Unity e hoʻōki i ka lilo ʻana i mīkini pāʻani maʻemaʻe. No ka laʻana, hoʻohana ʻia ia e hoʻolilo i nā wikiō CGI: inā ʻoe e hoʻomohala nei i kahi kaʻa, no ka laʻana, a makemake ʻoe e hana i kahi hoʻolaha, makemake ʻoe e hana i kahi wikiō maikaʻi. Ua lohe au ua hoʻohana ʻia ʻo Unity no ka hoʻolālā hale. ʻO ia hoʻi, ma nā wahi āpau e pono ai ka nānā ʻana, hiki ke hoʻohana ʻia ka Unity. Inā ʻoe e google, hiki iā ʻoe ke loaʻa nā hiʻohiʻona hoihoi.

Inā makemake ʻoe e nīnau, e ʻoluʻolu e ʻike iaʻu ma nā pūnaewele kaiapili āpau.

Ka mea i hana mua

  1. ʻO Ilona Papava, Luna Pūnaewele Nui ma Facebook - pehea e loaʻa ai kahi internship, loaʻa kahi hāʻawi a me nā mea āpau e pili ana i ka hana ʻana i ka ʻoihana.
  2. ʻO Boris Yangel, ʻenekinia ML ma Yandex - pehea e hui ʻole ai i ka pae o nā loea leo inā he ʻepekema ʻikepili ʻoe
  3. Alexander Kaloshin, Luna Nui LastBackend - pehea e hoʻomaka ai i kahi hoʻomaka, komo i ka mākeke Kina a loaʻa iā 15 miliona mau kālā.
  4. Natalya Teplukhina, Vue.js lālā hui nui, GoogleDevExpret - pehea e hele ai i kahi ninaninau ma GitLab, e komo i ka hui hoʻomohala Vue a lilo i Staff-engineer.
  5. ʻO Ashot Oganesyan, ka mea hoʻokumu a me ka luna ʻenehana o DeviceLock - nāna i ʻaihue a loaʻa kālā ma kāu ʻikepili pilikino.
  6. ʻO Sania Galimova, mea kūʻai ma RUVDS - pehea e ola ai a hana pū me kahi maʻi psychiatric. ʻĀpana 1. ʻĀpana 2.
  7. ʻO Ilya Kashlakov, ke poʻo o ke keʻena mua o Yandex.Money - pehea e lilo ai i alakaʻi o ka hui mua a pehea e ola ai ma hope o kēlā.
  8. ʻO Vlada Rau, ka mea kākau kiʻi kiʻi kiʻi kiʻi ma McKinsey Digital Labs - pehea e loaʻa ai kahi internship ma Google, hele i ke kūkākūkā a neʻe i Ladana.
  9. ʻO Richard "Levellord" Gray, ka mea nāna i hana i nā pāʻani Duke Nukem 3D, SiN, Blood - e pili ana i kona ola pilikino, nā pāʻani punahele a me Moscow.
  10. ʻO Vyacheslav Dreher, ka mea hoʻolālā pāʻani a me ka mea hana pāʻani me 12 mau makahiki o ka ʻike - e pili ana i nā pāʻani, ko lākou ola a me ka monetization
  11. ʻO Andrey, ka luna ʻenehana ma GameAcademy - pehea e kōkua ai nā pāʻani wikiō iā ʻoe e hoʻomohala i nā mākau maoli a loaʻa kāu hana moeʻuhane.
  12. ʻO Alexander Vysotsky, alakaʻi i ka mea hoʻomohala PHP ma Badoo - pehea e hana ʻia ai nā papahana Highload ma PHP ma Badoo.
  13. ʻO Andrey Evsyukov, Hope CTO ma Delivery Club - e pili ana i ka hoʻolimalima ʻana i 50 mau mea kahiko i nā lā 43 a pehea e hoʻomaikaʻi ai i ka hoʻolālā hoʻolimalima.
  14. ʻO John Romero, ka mea nāna i hana i nā pāʻani Doom, Quake a me Wolfenstein 3D - nā moʻolelo e pili ana i ka hana ʻana o DOOM
  15. ʻO Pasha Zhovner, ka mea nāna i hana ʻo Tamagotchi no nā hackers Flipper Zero - e pili ana i kāna papahana a me nā hana ʻē aʻe.
  16. ʻO Tatyana Lando, ka mea loiloi linguistic ma Google - pehea e aʻo ai i ke ʻano kanaka kōkua Google
  17. ʻO ke ala mai ka ʻōpio a i ka luna hoʻokō ma Sberbank. Nīnauele me Alexey Levanov

Pehea e kūʻai aku ai ʻo Data Science iā ʻoe i ka hoʻolaha? Nīnauele me kahi ʻenekini Unity

Pehea e kūʻai aku ai ʻo Data Science iā ʻoe i ka hoʻolaha? Nīnauele me kahi ʻenekini Unity

Source: www.habr.com

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