Emuva ngo-2012, i-HBR ibizwa ngokuthi "usosayensi wedatha" njengomsebenzi "obaluleke kakhulu wekhulu leminyaka." Kodwa ngempela i-data yesayensi ihilela ngempela? Futhi okubaluleke kakhulu, ungayithola kanjani amakhono adingekayo ukuze uzibize usosayensi wedatha?
Kuyini i-Data Science?
Ngesinye isikhathi, ososayensi bezinkampani bebaningi esikhaleni semfundo. Manje, ngokukhuphuka kokuqoqwa kwedatha enkulu kanye nesidingo sokuhlaziywa, ososayensi be-data baye baba nesidingo esiphakeme ezinkampanini eziningi nezinkampani, ezincane nezinkulu.
Isayensi yesayensi njengomsebenzi ihlanganisa amakhono amaningi ngaphakathi kwezibalo, izibalo kanye nokuhlelwa kwekhompyutha. Yimboni elawulwa yindoda, ukulinganiswa kwabesifazane besayensi ye-data kuyi-10%.
Ngokusho kwe-Glassdoor, umholo kazwelonke wesayensi ososayensi u-$ 113,436. Uma ubheka isinxephezelo yedwa, isayensi ye-data iyakhanga kakhulu kuneminye imisebenzi efana nayo.
Amakhono adingekayo ukuba abe Scientist Data
Njengamanye imisebenzi, amakhono athile adingekayo ukugcwalisa izikhundla zesayensi zesayensi ancike enkampanini ngayinye.
Kodwa kunamakhono athile / amathuluzi esofthiwe ahlala angaguquki.
- Izilimi zokuhlela izibalo, njenge-R ne-SAS
- Ulimi lokuzama ukusebenzisa idatha njengeSQL
- Izibalo eziyisisekelo ezifana nezivivinyo zezibalo, ukunikezwa, izilinganiso eziphezulu zokuphila, njalonjalo
- Izindlela zokufunda zomshini ezifana ne-k-Omakhelwane abaseduze, amahlathi angahleliwe, izindlela zokuhlanganisa, njll.
- Ukubala okungaxhunywanga kanye ne-algebra eqondile
- Ukufakwa kwedatha nokuthuthukiswa kwemikhiqizo emisha eqhutshwa kwedatha
- Ukujwayela nge-platform ye-Hadoop
- Amathuluzi wokubukwa njenge-Flare, HighCharts noma ama-AmCharts
Indlela Yokuba Usosayensi Wez Data
Namuhla, kunezinketho ezintathu ezisebenzayo zokuba usosayensi wedatha:
- Ukuzifundela ngezinhlelo ezinjengobudlova
- Ukuya ekamu le-boot yesayensi yedatha
- Ukuya esikoleni ukuphothula isiqu se-master degree
Yiqiniso, kunezinzuzo nezindleko kuleyo ndlela ngayinye.
Ukuzifundela
Izinzuzo:
- Kulula: kungenziwa ngesikhathi sakho kunoma imuphi imvelo nanganoma yiliphi ijubane
- Ingahambelani: ingadla noma kuphi kusuka ku- $ 0-600.
- Igcina isikhathi: izifundo ze-intanethi zingagcwaliswa phakathi nezinyanga ezingu-8-18.
Umthengi:
- Yamukela isitifiketi kuphela ngemuva kokuqedwa
- Akukho ukubandakanyeka kontanga noma othisha nomfundi
- Akukho usizo lokuzingela umsebenzi
I-Data Science Boot Camp
Izinzuzo:
- Ukuzibophezela kancane: kungagcwaliswa emavikini ayisithupha kuya kwezinyanga ezintathu
- Okungabizi kahle, okungenani kuqhathaniswa nokuthola i-master degree (amakamu okuqhafaza avela mahhala - $ 16,000)
- Kuhle kulabo abafuna ukushintsha imisebenzi ngokushesha
- Amakamu amaningi amabhuthoni anikeza usizo ekusebenziseni umsebenzi emva kokuqedwa
Umthengi:
- Thola kuphela iphothifoliyo yamaphrojekthi - akukho okuhlangenwe nakho "kwangempela" komsebenzi
- Okuningi okufanele ufunde ngesikhathi esincane
- Kungaba amahora angaba ngu-40 ngesonto lomsebenzi (ngokungafani nokuzihlola lapho ungaya khona ngesivinini sakho futhi usasebenza isikhathi esithile / isikhathi esigcwele)
Isiqu esiphezulu
Izinzuzo:
- I-Diploma ekupheleni
- Ukufunda okuhlelekile nabafundisi abaqeqeshwe kahle
- Okuhlangenwe nakho kwe-Real-world: izinhlelo eziningi zibandakanya izitejista ezizofaka ulwazi nolwazi
- Isikhathi esiningi sokufunda nokwamukela yonke imininingwane
Umthengi:
- Ezindleko: zingabiza phakathi kuka-R20 000- $ 70,000 - hhayi ukufaka izindleko zokuphila
- Ukudla isikhathi: kungathatha izinyanga ezide kakhulu (izinyanga ezingu-9-20)