"Inā he hui lawelawe kālā e nānā ana e hōʻemi i ka pilikia a i ʻole kahi mea kūʻai aku e hoʻāʻo nei e wānana i ka ʻano o ka mea kūʻai aku, ʻo ka AI a me ke ʻano aʻo mīkini e hoʻokumu ʻia ma kahi hoʻolālā ʻikepili kūpono," wahi a Ryohei Fujimaki, ka mea hoʻokumu o dotData a me ka ʻepekema noiʻi ʻōpio loa. moʻolelo o ka 119-makahiki IT hui NEC.
Ke piʻi aʻe nei ka makemake, pēlā nō ka nui o nā papahana ʻIke ʻIkepili ma nā kulanui. He aha nā modula e aʻo ai nā haumāna, he aha nā manawa visa i hāʻawi ʻia no nā haumāna puka kulanui - e nānā mākou ma lalo.
Ke Kulanui ʻo Radbound, Holland
ʻO ka haʻahaʻa papa o ka haku he 120 mau hōʻaiʻē, ʻelua makahiki o ke aʻo ʻana. I ka makahiki mua o ka hoʻonaʻauao kūikawā, lawe nā haumāna i ʻelima mau papa e pono ai (Machine Learning in Practice, Information Retrieval, Bayesian Networks, Research Seminar in Data Science, Philosophy and Ethics for Computing and Information Science). ʻO ke koena o ka papahana he electives, internships, a me ka hana dissertation. Aia nā papa koho: Nā Pūnaehana Naʻauao i ka Medical Imaging, Machine Learning in Particle Physics and Astronomy, Law in Cyberspace a me nā mea ʻē aʻe.
Hana ʻia nā internships ma nā ʻoihana liʻiliʻi a me nā liʻiliʻi liʻiliʻi, nā hui honua (ING Bank, Philips, ASML, Capgemini a i ʻole Booking.com), nā hui aupuni a i ʻole ma kekahi keʻena kahi e hana ai lākou me ka ʻikepili nui (astronomy, particle physics, neurobiology, bioinformatics. ).
Nā kūlana visa no nā haumāna puka: Ma hope o ka puka ʻana, hiki i nā haumāna ke noho ma ka ʻāina a hiki i 12 mau mahina e ʻimi i ka hana.
Ke Kulanui ʻo Simon Fraser, Kanada
He papahana laepua ka Data Science ma ke kulanui. Manaʻo ke kulanui i nā haumāna makemake e loaʻa ka hoʻonaʻauao postgraduate e noʻonoʻo i ka papahana o ka haku ʻoihana - Computer Science (Big Data). Hoʻomohala ʻo ia i nā loea ʻikepili ʻikepili, nā mea kākau ʻikepili a me nā luna ʻikepili koʻikoʻi hiki ke hāʻawi i nā ʻike e pili ana i ka hoʻoholo hoʻoholo.
ʻO ka hoʻomaʻamaʻa ʻana he 4 semesters (a i ʻole 16 mau mahina), me kahi internship uku ʻia he 4 mau mahina. Lawe nā haumāna a pau i nā papa kumu ma ke aʻo ʻana i ka mīkini, ka hoʻolālā a me ka nānā ʻana o nā algorithm no ka ʻikepili nui, ka ʻikepili ʻikepili, nā ʻōnaehana ʻikepili nui, ka hana ʻōlelo kūlohelohe. Kōkua nā labs koi i ke aʻo ʻana i nā ʻano like ʻole a me nā algorithm e pili ana i ka ʻikepili nui. Lawe nā haumāna i ʻelua papa papahana Programming for Big Data lab a loaʻa i ka SFU's Big Data Center, i wehe ʻia ma 2017 e hui pū i nā ʻoihana a me nā ʻoihana makemake i ka holomua ʻana i ka ʻoihana.
Nā kūlana visa no nā haumāna puka: No ka loaʻa ʻana o ka Palapala Hana Hana ma hope o ka puka ʻana, pono ʻoe e lilo i haumāna piha ma kekahi kulanui aupuni a i ʻole ke kulanui no ka liʻiliʻi o 8 mahina (900 mau hola) a hoʻopau pono i kāu papahana. Inā ʻoi aku ka lōʻihi o ka papa ma mua o 2 mau makahiki, a laila e hāʻawi ʻia ka Palapala Hana Ma hope o ka puka ʻana no 3 mau makahiki, inā ʻoi aku ka liʻiliʻi, a laila e like ka lōʻihi o ka manawa kūpono me ka papa hoʻomaʻamaʻa.
Kulanui o Veremona, USA
ʻO Master's in Complex Systems and Data Science he papahana ʻelua makahiki kahi e aʻo ai nā haumāna i nā ʻano o ka hōʻiliʻili, mālama ʻana a me ka hoʻoili ʻana i ka ʻikepili; ʻenehana hiʻohiʻona me ka nānā ʻana i ka hana ʻana i nā noi pūnaewele kiʻekiʻe. Ke nānā nei lākou i nā hiʻohiʻona paʻakikī a me ka hoʻoponopono ʻana, no ka laʻana, me ka hoʻohana ʻana i ka mīkini aʻo a me ka mining data, etc.
Loaʻa i nā modula kumu (12 mau hōʻaiʻē) nā ʻano aʻo e like me nā Principles of Complex Systems, Modelling Complex Systems, QR: Data Science, Data Science II.
Nā kūlana visa no nā haumāna puka: Hiki iā lākou ke hana i kahi hana hoʻomaʻamaʻa ʻo Optional Practical Training (OPT) i kā lākou ʻoihana kūikawā ma hope o ka loaʻa ʻana o kahi kekelē, ʻoiaʻiʻo, hana ma kahi visa aʻo. Ua kaupalena ʻia ka mana hana ma lalo o OPT i 12 mahina. Akā, no ka poʻe ʻōpio me kahi STEM nui, ua hoʻonui ʻia kēia manawa i 36. ʻO ka nūhou maikaʻi ma hope o kēia manawa, hiki iā ʻoe ke hoʻi i ke kulanui, no ka laʻana, ke kula master a i ʻole ke kula puka, aʻo no hoʻokahi makahiki a ʻelua paha a noi. no ka OPT hou. ʻO kahi koho ʻē aʻe e noho ai ma ka ʻāina ʻo ke noi ʻana i kahi visa hana H-1B inā loaʻa iā ʻoe kahi hui hana.
Ke Kula Nui ʻo Cork, ʻIlelani
ʻO ke kēkelē laeoʻo makahiki hoʻokahi ma Data Science a me Analytics ka hopena o ka hui pū ʻana ma waena o nā keʻena o ka ʻepekema kamepiula a me nā helu. Hāʻawi i ka ʻike i nā kumu kumu o kēia kahua e ulu wikiwiki nei. Pono nā haumāna e hoʻopiha i nā hōʻaiʻē 90 ma o ka hui pū ʻana o nā modules (Data Mining, Deep Learning, Foundations of Statistical Data Analytics, Generalized Linear Modelling Techniques, Database Technology), electives (Optimization, Information Storage and Retrieval, Machine Learning and Statistical Analytics, Scalable Computing. no ka ʻikepili ʻikepili a me nā mea ʻē aʻe) a me nā dissertation. Ua ʻae ʻia nā modules elective a pau e ka curator program.
Ua hoʻohana ʻia nā haumāna puka o 2017-2018 e nā hui e like me Amazon, Apple, Bank of Ireland, Dell, Digital Turbine Asia Pacific, Dell EMC, Enterprise Ireland, Ericsson, IBM, Intel, Pilz, PWC.
Nā kūlana visa no nā haumāna puka: Ua hoʻomohala ʻia ka papahana kula kiʻekiʻe ʻekolu no ka poʻe ʻōpio mai waho o ka European Union. Loaʻa i nā haumāna puka a pau o nā kulanui i ʻae ʻia ka ʻae ʻia e noho ma ka ʻāina no 12 mahina, a ʻo ka poʻe i pau i ke kula master a postgraduate hiki ke hoʻopaneʻe i kā lākou visa no 12 mahina.
Ke Kulanui o Portsmouth, UK
Ma hope o ka hoʻopau ʻana i ke kēkelē laepua ma ka Data Analytics, e hoʻolako ʻia kahi haumāna me nā mea hana eli ʻikepili a me ka ʻike pehea e hoʻopili ai iā lākou i ka noiʻi ʻana i nā kahua o ka cosmology, mālama olakino, a me ka cybersecurity. ʻO ka lōʻihi o ke aʻo ʻana he 12 mau mahina, pono ʻoe e loaʻa i nā hōʻaiʻē 180. Nā modula kumu: Hoʻopili ʻia i ka ʻikepili a me ka helu kikokikona, nā noi ʻikepili nui, ka ʻike ʻoihana, ka hoʻokele ʻikepili, ka ʻenekinia kumu a i ʻole ka papahana haʻawina.
No ka poʻe makemake e komo koke i kahi internship i kā lākou ʻoihana kūikawā ma ke kulanui, aia kahi papahana haku me ka ʻike ʻoihana. He 18 mau mahina, me 6 mau mahina o ka hoʻomaʻamaʻa i hoʻohui ʻia i nā haʻawina. Hoʻohui i ka manawa kūpono e hoʻopili i nā mea hana ʻikepili i nā ʻenehana hou a me nā hoʻomaka me ka hoʻohana ʻana i ka SAP Next Gen Lab.
Nā kūlana visa no nā haumāna puka: Hiki iā ʻoe ke noho ma ka ʻāina a hiki i 2 mau makahiki ma hope o ka hoʻopau ʻana i kāu mau haʻawina e ʻimi i kahi mea hana me ka laikini kākoʻo.
Source: www.habr.com