ʻO nā papahana Masters online maikaʻi loa ma Data Science e hoʻomākaukau i nā haumāna no kekahi mau ʻoihana e pili ana i ka hōʻiliʻili ʻana, ka unuhi ʻana, a me ka hoʻohana ʻana i ka ʻike e hoʻoponopono ai i nā pilikia o ka honua. Hiki i nā haumāna puka ke hana ma ke ʻano he ʻepekema data, data analyst, statistical analyst, a i ʻole ka noiʻi noiʻi mākeke, ma waena o nā ala ʻoihana ʻē aʻe.
ʻO ka ʻepekema ʻikepili kahi kahua o ke aʻo ʻana e hoʻohana ana i nā kaʻina ʻepekema, algorithms, a me nā ʻōnaehana e unuhi i ka ʻike a me nā ʻike mai ka nui o nā ʻikepili i kūkulu ʻia a i hoʻonohonoho ʻole ʻia.
Pono e hana ʻia ka ʻike i kahi ʻano i hiki ke hoʻomaopopo ʻia e nā kānaka a i ʻole nā mīkini. No ka loaʻa ʻana o ka haku pūnaewele maikaʻi loa i ka ʻepekema data, ua nānā mākou i nā mea koʻikoʻi no nā haumāna e hiki mai ana, ʻoi aku ka nui o nā wānana maʻamau o ka kūleʻa o ka wā e hiki mai ana a me ka hoʻokō ʻana o kahi kula i nā papahana pūnaewele.
Hoʻopili kēia i ka helu komo ʻana, ka helu paʻa o ka hōʻaiʻē haumāna, ka helu paʻa, ka helu puka ʻana, a me ka pākēneka o nā haumāna i kākau inoa ʻia i nā papa pūnaewele.
Lawe ʻia nā helu ʻikepili a pau mai ka ʻike i hāʻawi ʻia e nā koleke a me nā kulanui i ka National Center for Education Statistics.
Table of Contents
He aha ka ʻepekema ʻikepili?
ʻO ka ʻepekema ʻikepili kahi kahua aʻo e hoʻopili ai i ka makemakika, nā helu, a me nā ʻano ʻepekema ʻē aʻe e huki i nā hopena mai ka ʻikepili.
He aʻo hou kēia, akā he mea koʻikoʻi loa ia i kēia ao. Nui ka ʻike i mālama ʻia i loko o nā ʻikepili ma ka honua holoʻokoʻa, akā me ka ʻole o nā mākau a me nā mea hana e kālailai i kēlā ʻikepili, hiki ke paʻakikī ke ʻimi i nā ʻike pono.
Nui nā kulanui e hāʻawi i nā papahana ʻepekema data ma ke kula puka a me ke kula haʻahaʻa. Hoʻohui kēia mau papahana i ka hoʻomaʻamaʻa makemakika a me ka helu helu o ke kēkelē kuʻuna me nā papa hoʻolālā kamepiula, he mea nui ia no ka nānā ʻana i ka nui o ka ʻike i nā kūlana honua maoli.
No ka poʻe i loaʻa ke kēkelē laepua akā makemake lākou e holomua i kā lākou ʻoihana ma ka loaʻa ʻana o nā mākau quantitative hou aʻe, nui nā kekelē haku pūnaewele ma ka ʻepekema data i loaʻa ma nā kulanui a puni ka honua.
20 Masters maikaʻi loa ma ka ʻikepili ʻepekema ma ka pūnaewele
Aia ma lalo kahi papa e hōʻike ana i nā papahana Masters maikaʻi loa ma Data Science.
| S / N | kula | Program | kiʻekiʻe |
| 1 | Harvard University | Kumu ʻepekema ʻikepili | 1 |
| 2 | Ke Kulanui o New York | Master of Science (MS) ma ka ʻIke ʻIkepili | 2 |
| 3 | Ke Kulanui o Kaleponi, Berkeley | Kumu o ka 'ike a me ka 'ike 'ike | 2 |
| 4 | Ke Kulanui o ʻAmelika -ʻO ʻObbana-Champaign | Master of Computer Science in Data Science | 4 |
| 5 | Kulanui o Kaleponi Hema | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 4 |
| 6 | Kulanui o Wisconsin, Madison | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 4 |
| 7 | Ke Kulanuiʻo John Hopkins | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 7 |
| 8 | Northwestern University | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 8 |
| 9 | Hawaiian Methodist University | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 8 |
| 10 | Ke KulanuiʻO Indiana University Bloomington | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 10 |
| 11 | Kulanui o Notre Dame | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 10 |
| 12 | ʻO Rochester Institute of Technology | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 10 |
| 13 | Ke Kulanui o Virginia, Charlottesville | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 13 |
| 14 | Ke Kula Nuiʻo Boston | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 14 |
| 15 | Kulanui o Michigan | Kumu o ka ʻIkepili ʻIkepili ʻepekema | 15 |
| 16 | Ke Kulanui o Villanova | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 15 |
| 17 | Kulanui o Colorado | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 15 |
| 18 | Kulanui o Kaleponi Kaleponi | Kumu Hoʻonaʻauao | 15 |
| 19 | Ke Kulanui DePaul | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 15 |
| 20 | Kulanui o North Dakota | Ka Papahana Hoʻonaʻauao iʻEpekemaʻIkepili | 15 |
1. Ke Kula Nui ʻo Harvard (Harvard Extension School)
ʻO ka pahuhopu o ka Master in Data Science ʻo ia ka hāʻawi ʻana i nā haumāna i ka ʻike ʻenehana a me ka ʻike kumu e hiki ai ke hoʻolālā, hoʻomohala a loiloi i nā hopena pili i ka ʻikepili e kōkua i nā hui e hana i nā hoʻoholo maikaʻi aʻe a lawe i ka waiwai mai kā lākou ʻikepili.
Aia kēia papahana i nā papa kumu e pili ana i ka ʻepekema data, a me nā modules elective e ʻae ai i ka hana kūikawā ma nā wahi like ʻole e like me ke aʻo ʻana i ka mīkini, ka ʻike artificial, a i ʻole ka ʻoihana ʻoihana. Hoʻokomo pū ka papahana i ka hoʻomohala ʻana i kahi papahana hope, pono ke kumuhana e pili i ke kahua o ka ʻepekema data.
Hoʻokahi makahiki kula (60 ECTS) ke kēkelē laeoo a he ʻekolu kau kau. Hiki i nā haumāna ke koho ma waena o ke aʻo ʻana he alo a he alo paha.
No ka hoʻopau ʻana i kahi papa papa i hui ʻia, pono nā haumāna e hele i nā hālāwai pūnaewele i kēlā me kēia pule a hele i kahi hoʻokolokolo hope ma ka hopena o ke kau.
2. Ke Kulanui o New York, Stern School of Business
Loaʻa nā papahana a ka haku ʻepekema ʻikepili ma ke ʻano he Master of Science (MS) i ka ʻIke ʻIke, Master of Computer Science in Data Science, a i ʻole Master of Business Administration (MBA) me ka manaʻo i ka ʻepekema data.
ʻElua mau makahiki e hoʻopau ai ke kēkelē laepua ma ka ʻepekema data a hāʻawi pinepine ʻia ma ke ʻano he papahana hybrid, ʻo ia hoʻi e lawe nā haumāna i kekahi mau papa ma ka pūnaewele a me nā mea ʻē aʻe ma ka pā kula.
Pono nā papahana haku pūnaewele ma ka ʻepekema data i nā haumāna e hoʻopau i nā hōʻaiʻē 30-36. Hāʻawi ka hapa nui o nā papahana i ka manaʻo, e like me ke aʻo ʻana i ka mīkini a i ʻole ka naʻauao artificial.
I ke kau hope loa, koi ka hapa nui o nā papahana i nā haumāna e hoʻopau i kahi papahana capstone, kahi e hiki ai iā lākou ke hōʻike i ko lākou mākaukau i nā mākau ʻepekema data a me nā manaʻo.
No ke kākau inoa ʻana i kahi papahana haku pūnaewele ma ka ʻepekema data, pono e loaʻa i nā mea noi ke kēkelē laepua mai kahi kula i ʻae ʻia me ka liʻiliʻi he 3.0 GPA.
ʻAʻole koi ka hapa nui o nā kula i nā haumāna e hoʻouna i nā helu GRE, akā noi paha kekahi i nā mea noi e hoʻouna i nā helu GRE inā ʻoi aku ko lākou GPA ma lalo o 3.0. Pono kekahi mau kula i nā mea noi e hāʻawi i nā leka kākoʻo a me kahi ʻōlelo o ka moʻolelo kumu.
3. Ke Kulanui o Kaleponi, Berkeley
ʻOiai ka hoʻokūkū ʻana mai ka Ivy League a me nā ʻoihana ʻenehana i manaʻo ʻia, ʻo ke Kulanui o Kaleponi, ʻo Berkeley ka mea i hoʻopaʻa mau ʻia ma ke ʻano he kulanui aupuni kiʻekiʻe loa ma ʻAmelika Hui Pū ʻIa a ua hoʻopaʻa pinepine ʻia i waena o nā kula kiʻekiʻe he ʻumi.
Aia ʻo Berkeley i kekahi o nā papahana ʻepekema ʻikepili kahiko loa a piha loa i ka ʻāina, me kona kokoke i ka moku ʻo San Francisco Bay a me Silicon Valley e hāʻawi ana i kona kūlana kiʻekiʻe.
Hoʻolimalima pinepine ʻia nā haumāna puka o kēia kula i nā ʻoihana hoʻomaka a hoʻokumu ʻia ma ka honua holoʻokoʻa, kahi i kaulana loa ai ka pūʻulu ʻepekema data.
Ke aʻo nei nā kumu kula me ka ʻike ʻoihana i nā hui ʻepekema data ma ia wahi i nā papa, e hoʻokomo piha ana i nā haumāna puka i nā manaʻolana o kā lākou hana ma ka ʻāpana.
4. Kulanui o Illinois Urbana Champaign
Ke kūlana mau nei ke Kulanui o Illinois ma Chicago (UIUC) ma waena o nā papahana ʻepekema kamepiula ʻelima kiʻekiʻe ma US, ma mua o ka Ivy League, nā kula ʻenehana pilikino, a me nā mea ʻē aʻe. Ua puni ka papahana ʻepekema ʻikepili ma ka pūnaewele no ʻekolu mau makahiki, me ka nui o ia mea i hoʻohui ʻia i Coursera.
ʻO kā lākou kumukūʻai ka haʻahaʻa loa ma waena o nā papahana DS kiʻekiʻe, ma lalo o $ 20,000. Ma waho aʻe o ka maikaʻi o ka papahana, kūlana, a me ka waiwai, paʻakikī ka haʻawina a hoʻomākaukau i nā haumāna no kahi ʻoihana maikaʻi ma ka ʻepekema data, e like me ka hōʻike ʻana e nā alumni e hana ana i nā ʻoihana like ʻole a puni ʻAmelika Hui Pū ʻIa.
5. Kulanui o Kaleponi Hema
ʻOiai ke kumu kūʻai kiʻekiʻe, hoʻohana koke ʻia nā haumāna puka mai ke Kulanui o Southern Kaleponi (USC) ma kekahi o nā wahi hoʻokipa ʻepekema data nui loa o ka honua - ʻo Kaleponi hema.
Hiki ke loaʻa nā alumni o kēia papahana i nā hui ma ka ʻāina, me San Diego a me Los Angeles. ʻO ka papa haʻawina kumu he 12 wale nō ʻāpana, a i ʻole ʻekolu papa, me nā ʻāpana ʻē aʻe he 20 i māhele ʻia i ʻelua pūʻulu: Pūnaehana ʻIkepili a me ʻIkepili ʻIkepili. Paipai ʻia nā ʻenehana loea me ka ʻike ʻoihana e noi.
6. Kulanui o Wisconsin, Madison
Ua loaʻa iā Wisconsin kahi papahana pūnaewele no nā makahiki a, ʻaʻole e like me nā kula kiʻekiʻe kiʻekiʻe, pono kahi papa capstone. He multidisciplinary ka papahana, e like me ka hoʻokele, kamaʻilio, ʻikepili, makemakika, a me nā kumuhana ʻepekema kamepiula.
Manaʻo maikaʻi ʻia kā lākou kumu kula, me nā kauka kauka ma nā ʻano ʻano like ʻole me ka naʻauao artificial, ka ʻepekema kamepiula, a me nā helu helu, a me ka ʻike nui o ka ʻoihana a me ka hoʻonaʻauao ma ke kālepa.
Loaʻa paha nā Alumni ma nā kūlanakauhale nui a puni ʻo ʻAmelika Hui Pū ʻIa, a hāʻawi ʻia i ke kumu kūʻai maʻalahi, he waiwai maikaʻi kēia papahana haku pūnaewele.
7. Ke Kulanuiʻo John Hopkins
No nā kumu like ʻole, ʻo John Hopkins kekahi o nā haku pūnaewele waiwai nui i nā papahana ʻepekema data. No ka hoʻomaka, hāʻawi lākou i nā haumāna a hiki i ʻelima mau makahiki e hoʻopau i ka papahana, he mea maikaʻi loa ia no nā mākua a me nā limahana manawa piha.
ʻAʻole manaʻo kēia ʻokoʻa he lohi ka papahana; hiki ke hoʻopau ʻia ma lalo o ʻelua makahiki. Ua kaulana ʻia ke kulanui no ka hoʻouna ʻana i nā alumni i kekahi mau wahi ʻākau hikina, ʻo Boston a me New York City.
No nā makahiki, ua hāʻawi ʻo John Hopkins i nā papa ʻepekema data a ua alakaʻi ʻo ia i ka hāʻawi ʻana i nā papa pūnaewele manuahi, hoʻonui i ka inoa o ka papahana, mākaukau e aʻo i ka ʻepekema data ʻokiʻoki, a me nā kūlana hana puka puka.
8. Northwestern University
ʻO ke Kulanui o Northwestern, ma waho aʻe o ke kulanui kūʻokoʻa kiʻekiʻe me nā alumni i ʻimi nui ʻia i nā ʻoihana ʻepekema data Midwest, hāʻawi i kahi ʻike aʻo kūʻokoʻa ma ka ʻae ʻana i nā haumāna e koho mai nā ʻoihana ʻehā. ʻO ka Analytics Management, Data Engineering, Artificial Intelligence, a me Analytics and Modelling nā laʻana o kēia.
Hoʻoulu ʻia kēia ala ʻokoʻa i ka launa pū ʻana me nā mea komo a me nā limahana aʻoaʻo, nāna e kōkua i nā haumāna matriculated i ke koho ʻana i kahi loea e pili ana i kā lākou makemake a me nā pahuhopu ʻoihana.
ʻO ka hoʻokō ʻana o Northwestern i nā haumāna ma mua o ke aʻo ʻana ma mua o ke kau inoa ʻana, me ka nui o ka ʻike ma kā lākou pūnaewele e kōkua i nā haumāna e noʻonoʻo inā kūpono ka papahana, me ka ʻōlelo aʻoaʻo e pili ana i nā ʻoihana ʻepekema data a me nā haʻawina.
Hoʻokumu ka papahana o ka papahana i ka ʻikepili wānana a me ka ʻaoʻao helu helu o ka ʻepekema data, ʻoiai aia kekahi mau kumuhana ʻē aʻe.
9. Hawaiian Methodist University
Ua hāʻawi aku ke kula kaulana ʻo Southern Methodist University (SMU) ma Dallas, Texas, i ke kēkelē laepua ma ka ʻikepili ʻikepili no kekahi mau makahiki, e piʻi ana ma ke ʻano he alakaʻi i ka hana ʻana i nā haumāna puka kiʻekiʻe ma ʻAmelika Hui Pū ʻIa.
Ua kūpaʻa ke kulanui i ka hāʻawi ʻana i ke kōkua ʻoihana i kāna mau haumāna puka āpau, me ka hoʻomaʻamaʻa ʻoihana a me kahi ʻoihana ʻoihana virtual me nā koho hana kūikawā no nā alumni SMU.
E loaʻa i nā haumāna puka ka manawa e launa pū ai a hana i nā pilina me nā ʻoihana kaulana ma Texas.
10. Ke KulanuiʻO Indiana University Bloomington
He waiwai kūʻokoʻa ka papahana o Indiana's Master of Science in Data Science online e ke kula aupuni nui ma Midwest, a he kūpono ia no ka poʻe ma waena o ka hana a makemake paha e hoʻololi i kahi ala kikoʻī o ka ʻepekema data.
He maʻalahi nā koi degere, me nā koho koho no ka hapalua o nā hōʻaiʻē 30 i koi ʻia. Hoʻoholo ʻia ʻeono o nā ʻaiʻē he kanakolu e ka ʻāpana kikowaena o ke kēkelē, ʻo ia hoʻi ʻo Cybersecurity, Precision Health, Intelligent Systems Engineering, a me Data Analytics and Visualization.
Eia kekahi, paipai ʻo Indiana i kā lākou mau haumāna pūnaewele e komo i kahi manawa ʻoihana hōʻaiʻē ʻole ma ko lākou pā kula nui.
Hoʻopili ʻia nā haumāna i nā alakaʻi ʻoihana a me nā ʻoihana i ka makahiki 3-lā Online Immersion Weekend i ka pūnaewele a kūkulu i nā pilina ma mua o ka puka ʻana.
11. Kulanui o Notre Dame
Hāʻawi ke Kulanui o Notre Dame, kahi kula kaulana i ka honua, i kahi kekelē ʻepekema data kaulike kūpono no nā poʻe hoʻomaka.
ʻAʻole koi ko lākou mau kūlana hoʻokomo i nā mea noi e hoʻopau i kahi a nāʻikeʻepekema a i ʻole ka papahana laepua makemakika, ʻoiai hāʻawi lākou i kahi papa inoa o nā papa i manaʻo ʻia e kōkua iā lākou e hoʻomākaukau.
Ma Python, Java, a me C++, pono nā mākau helu helu liʻiliʻi wale nō, a me ka ʻike i nā kūkulu ʻikepili.
12. ʻO Rochester Institute of Technology
Ua kaulana ʻo Rochester Institute of Technology (RIT) no ka hoʻouna ʻana i nā alumni i ka Midwest a me Northeast. ʻO kā lākou kula pūnaewele, kahi i hoʻokumu ʻia ma ke komohana o New York, e hoʻoikaika i ka hoʻonaʻauao maʻalahi e pili ana i ka piʻi ʻana o ka pono o ka ʻenehana ʻepekema data.
Hiki ke hoʻopau ʻia ke kēkelē ma kahi liʻiliʻi o 24 mau mahina, a he ʻoluʻolu loa nā kūlana komo, me ka manaʻo o ka ʻepekema paʻakikī akā ʻaʻole pono nā hoʻokolohua maʻamau.
He moʻolelo lōʻihi ko RIT no ka hoʻomākaukau ʻana i nā haumāna e lilo i mau alakaʻi ʻoihana a he koho maikaʻi ia no ka poʻe e makemake ana e loaʻa i ka hoʻonaʻauao ʻepekema data ma kahi ʻenehana ʻenehana.
13. Kulanui o Virginia, Charlottesville, Virginia
Hāʻawi ke Kulanui o Virginia i kahi kekelē haku pūnaewele ma ka ʻepekema data.
Loaʻa i kēia kula ʻoihana ʻepekema ʻikepili pūnaewele maikaʻi loa kahi papahana i hoʻohui maikaʻi ʻia e koʻikoʻi i ke aʻo lima.
Hāʻawi ʻia nā haʻawina e nā kumu aʻoaʻo honua mai nā kula like ʻole a me nā keʻena. E pōmaikaʻi nā haumāna mai kahi kaiapuni cohort aloha e paipai ana i ka hana hui a me ke kūkulu ʻana i ka pūnaewele.
Aia ka papahana ʻelima semester i nā kumuhana e like me:
- papahana ʻōlelo kūlohelohe
- aʻo aʻo
- ʻikepili kikokikona.
Hana pū nā haumāna e hoʻokō i kahi papahana capstone hui, e hoʻomaʻamaʻa i kā lākou aʻo ʻana i ka lumi papa. No ke koho ʻana i ke komo ʻana, pono i nā mea noi ke loaʻa i ka nui o ka quantitative a me ka hiki ke kamaʻilio.
14. Kula Nui ʻo Boston - ʻo Bosetona, Massachusetts
Me kāna MS i Applied Data Analytics, hāʻawi ʻo Boston University i kekahi o nā papahana ʻepekema data pūnaewele maikaʻi loa.
Hoʻolālā ʻia ka papahana no ka poʻe loea IT i kā lākou ʻoihana waena e makemake e aʻo e pili ana i nā mea hana ʻoihana hou a me nā ʻano hana i kahi kūlana hoʻonaʻauao koʻikoʻi.
ʻO nā kumu kula kiʻekiʻe PhD a me nā loea me nā makahiki o ka ʻoihana ʻoihana e aʻo i nā papa ma ka papahana ʻepekema data noiʻi. Hana nā haumāna i nā papahana lima lima i loko o ka papa e kūkulu i kahi kōpili o nā hana i hoʻopaʻa ʻia e hōʻike i ko lākou hiki ke hoʻopaʻa inoa.
15. Ke Kulanui o Michigan - Ann Arbor, Michigan
No nā haumāna e ʻimi nei i kahi ʻike kūpono a maʻalahi hoʻi, hāʻawi ke Kulanui o Michigan i ka Master of Applied Data Science Online, kekahi o nā papahana ʻepekema data pūnaewele kiʻekiʻe.
E aʻo ana nā haumāna i ka hoʻohana ʻana i ka ʻikepili no ka hoʻoponopono ʻana i nā pilikia ma kekahi mau ʻoihana a me nā ʻoihana.
Hāʻawi nā haʻawina i nā kumuhana e like me:
- hōʻiliʻili waihona
- ka helu a me ka ʻikepili
- helu helu.
E loaʻa i nā haumāna ka ʻike kūpono ma o ka papa hana a me nā papahana i hoʻopili ʻia e hoʻoponopono i nā pilikia o ka honua maoli. ʻAʻohe koi noho ma ka pā kula.
16. Ke Kulanui ʻo Villanova – Villanova, Pennsylvania
Ua hoʻokumu ke Kulanui ʻo Villanova i kāna papahana kiʻekiʻe kiʻekiʻe o ka ʻepekema data ʻepekema master's degere no ka hoʻomohala ʻana i nā alakaʻi loiloi ʻoihana i hoʻomaʻamaʻa maikaʻi ʻia.
Hōʻike ka papahana i nā pono ʻoihana a me nā ʻoihana o kēia manawa.
Hāʻawi ka papa hana i nā wahi e komo pū ana:
- ʻIke ʻike ʻoihana
- Nā hiʻohiʻona wānana a me ka prescriptive
- Hoʻoponopono ʻikepili.
Aʻo ʻia nā haʻawina e nā kumu ʻike ʻoihana i hoʻomaopopo i ke ʻano ʻoihana o kēia manawa. Hāʻawi kahi papahana capstone me kahi hui i nā haumāna i ka manawa e hoʻoponopono ai i nā pilikia o ka honua maoli a loaʻa ka ʻike lima lima.
Hiki i nā haumāna ke hoʻopau i kā lākou mau kekelē holoʻokoʻa ma ka pūnaewele i loko o 24 mau mahina.
17. Ke Kulanui o Colorado – Boulder, Colorado
ʻO ke kula kiʻekiʻe o ke Kulanui o Colorado Boulder ma ka ʻEpekema ʻIkepili he kekelē interdisciplinary i hāʻawi ʻia ma o ka papahana aʻo ʻo Coursera.
Ma muli o ke ʻano o ka hoʻokomo ʻana i ka hana, hiki i nā haumāna ke hoʻomaka e hana i kā lākou kekelē koke me ka ʻole e waiho i kahi palapala noi a i ʻole transcripts.
ʻO nā kumu kula kiʻekiʻe e aʻo ana ma ka pā kula e aʻo i nā papa. E pōmaikaʻi ka poʻe ʻoihana hana mai nā huaʻōlelo ʻewalu pule a me nā papa hana ponoʻī.
Lawe nā haumāna i 30 mau hola ʻaiʻē o ka haʻawina, ʻo ia hoʻi nā papahana lima lima e kōkua iā lākou e hoʻomohala i nā mākau ʻoihana.
ʻO ka hapa nui o nā haumāna e hoʻopau i kā lākou mau kekelē i loko o ʻelua mau makahiki.
18. Ke Kulanui o Kaleponi Riverside – Riverside, Kaleponi
Hiki i nā haumāna ke loaʻa kahi MS pūnaewele kūpono ma ka ʻenekinia me ka nānā ʻana i ka ʻIke ʻIkepili mai ke Kulanui o Kaleponi Riverside ma kahi o 13 mau mahina.
Loaʻa ka papahana ma ka pūnaewele, ʻaʻohe koi no ka hele ʻana ma ka pā kula. Lawe nā haumāna i 16 mau hōʻaiʻē o ka ʻenekinia a me 16 mau hōʻaiʻē o nā papa ʻepekema data, e ʻae iā lākou e hoʻopilikino i ke kēkelē i ko lākou makemake ʻoihana.
Aia nā haʻawina i ka ʻepekema data:
- Helu Heluhelu
- Ka Papa Hana
- ʻIke ʻIke a me ka Huli Pūnaewele.
Hāʻawi nā papa Capstone i nā haumāna i kahi ʻike aʻo waiwai. Loaʻa i nā haumāna puka ʻenekinia ʻepekema ka mākaukau e pono ai no nā manawa ʻoihana like ʻole ma nā ʻāpana ʻoihana like ʻole.
19. Ke Kulanui ʻo DePaul - Chicago, Illinois
Hāʻawi ke Koleke o Computing a me Digital Media ma ke Kulanui ʻo DePaul i kahi papahana kiʻekiʻe kiʻekiʻe o ka ʻepekema ʻepekema ʻikepili pūnaewele e hāʻawi ana i ke kiʻekiʻe o ke koʻikoʻi e like me kā lākou papahana ma ka pā kula.
Hoʻopili nā papa i nā wahi e like me:
- Hoʻohālike helu
- Hoʻopili data
- BigʻIkepili
- Waihona ʻikepili.
ʻO kahi thesis a i ʻole internship ʻelua mau capstone koho e hiki ke kōkua i nā haumāna e hoʻokō i kā lākou mau pahuhopu hoʻonaʻauao a ʻoihana. Loaʻa nā ʻōlelo aʻoaʻo kumu a me nā lawelawe ʻoihana i nā haumāna pūnaewele e kōkua iā lākou i ka wā o kā lākou papahana a ma waho.
Hoʻomaka kēlā me kēia hapaha kau inoa me ke komo ʻana o nā haumāna hou.
20. Ke Kulanui o North Dakota – Grand Forks, North Dakota
Hiki i ke Kulanui o North Dakota ka papahana kumu ʻepekema data haʻahaʻa ke kōkua iā ʻoe e loaʻa nā mākau ʻikepili a nā ʻoihana kiʻekiʻe e ʻimi nei.
Hiki i nā haumāna ke hoʻopau i ka papahana 30-credit-hour i ʻelua mau makahiki me ka ʻole o ke kau wāwae ʻana ma ka pā kula. Hiki iā lākou ke hoʻololi i ke kēkelē e hoʻohālikelike i kā lākou mau pahuhopu ʻoihana ma o ka lawe ʻana i nā papa koho i nā wahi e like me ka ʻike ʻepekema a me ka palekana cyber.
Hiki i nā haumāna ke komo i ka noiʻi ʻokiʻoki i ka ʻenehana loea kiʻekiʻe a me nā ʻōnaehana lewa ʻole. Mākaukau nā haumāna puka e hana me nā pūʻulu ʻikepili nui ma nā ʻano ʻoihana like ʻole a me nā pōʻaiapili hoʻonohonoho.
Nā nīnau i nīnau pinepine ʻia e pili ana i nā Masters i ka ʻepekema data ma ka pūnaewele
He aha ka ʻepekema ʻikepili?
ʻO ka ʻepekema ʻikepili kahi kumuhana interdisciplinary e pili ana i ka makemakika, ka helu, a me ka ʻepekema kamepiula. Hoʻopili pū ʻia ka ʻike domain i mea e hoʻoponopono ai i nā pilikia paʻakikī e pili ana i ka ʻikepili.
He aha ka mea e ʻike ai kēlā me kēia ʻepekema data?
Pono ka ʻike maikaʻi o ka makemakika, ka noʻonoʻo ʻikepili, ka ʻepekema kamepiula, a me ka ʻepekema ʻikepili e lilo i ʻepekema data. Pono ʻoe e ʻike i ka hoʻomaopopo ʻana a me ka haʻi ʻana i nā hopena helu helu, a me nā manaʻo helu helu a me nā ʻano.
He aha ka hope o ka ʻepekema data?
E noʻonoʻo i ka piʻi ʻana o ka ʻikepili i hana ʻia e IoT a i ʻole ka ʻikepili pili i ka lihi. Ke nānā aku nei i mua, manaʻo ka US Bureau of Labor Statistics e loaʻa ana he 11.5 miliona mau hana ma ka ʻepekema data a me ka analytics e 2026-ma kahi o ʻeono makahiki mai kēia manawa.
He aha kou hoihoi i ka ʻepekema data?
E hoʻomaka ma ka kaʻana like ʻana i kou makemake i ka ʻikepili. Hiki iā ʻoe ke hōʻike i kou hoihoi ma ka wehewehe ʻana i ka mea i huki iā ʻoe i ke kula. No ka laʻana, hiki iā ʻoe ke haʻi e hauʻoli ʻoe i ka hoʻoponopono pilikia a me ka nānā ʻana i ka helu helu, i alakaʻi iā ʻoe i kahi ʻoihana ma ka ʻepekema data.
Hiki i ka ʻepekema data ke hana mai ka home?
ʻAe. ʻO ka ʻepekema ʻikepili kekahi o nā ʻoihana kaulana loa i hiki ke hana ʻia mai ka home, a ua wānana ʻia ka ʻāpana e hoʻonui ʻia e 16% e 2028. Pono nā ʻepekema data, nā mea loiloi, a me nā ʻenekinia e nā hui ma nā ʻano ʻoihana like ʻole, me ka mālama olakino, kamaʻilio. , a me ka ʻikepili ʻikepili.
manaʻo paipai
- 20 Nā polokalamu ʻepekema ʻikepili maikaʻi loa ma ka pūnaewele
- ʻO 20 mau kula kiʻekiʻe ʻepekema ʻikepili maikaʻi loa ma ka honua
- 2 Makahiki Computer Science Degree Online
- 40 ʻEpekema ʻEpekema Paʻa Loa Loa Loa Loa
- Kiʻekiʻe 15 Online Computer Science Degree
- ʻO 10 Best Computer Science Bachelor Degree Online
- ʻO 50+ mau kulanui maikaʻi loa no ka ʻepekema kamepiula ma ka honua.
Panina
Paʻakikī ka hoʻonaʻauao kūlana ma muli o ke ʻano o ke kanaka.
ʻOiai makemake paha kekahi poʻe i kahi papa hana maʻalahi i hiki iā lākou ke mālama i ko lākou ʻohana i ka lā, makemake paha kekahi i kahi ala lima lima hou i hiki iā lākou ke ʻike i ke ʻano o kā lākou māla ma mua o ka hana ʻana.
Ua ʻike mākou ʻaʻole kūpono ka nui hoʻokahi i ka wā e pili ana i kā mākou kūlana a ʻo ia ke kumu e like me kā mākou i ʻōlelo ai i ka hoʻomaka.
ʻO nā kumu āpau a mākou i manaʻo ai ua kaupaona ʻia i mea e hāʻawi ai i kahi ʻike kikoʻī a hoʻoholo i ka 20 maikaʻi loa o nā pae haku pūnaewele ma ka ʻepekema data.