{"id":383,"date":"2019-06-06T07:08:32","date_gmt":"2019-06-06T06:08:32","guid":{"rendered":"http:\/\/cafe2sach.com\/?p=383"},"modified":"2019-06-06T14:09:32","modified_gmt":"2019-06-06T13:09:32","slug":"em-nhat-dinh-phai-tro-thanh-mot-data-scientist","status":"publish","type":"post","link":"https:\/\/cafe2sach.com\/index.php\/2019\/06\/06\/em-nhat-dinh-phai-tro-thanh-mot-data-scientist\/","title":{"rendered":"Em nh\u1ea5t \u0111\u1ecbnh ph\u1ea3i tr\u1edf th\u00e0nh m\u1ed9t Data Scientist"},"content":{"rendered":"\n

Nhi\u1ec1u b\u1ea1n nh\u1eafn tin h\u1ecfi m\u00ecnh v\u1ec1 vi\u1ec7c ch\u1ecdn ng\u00e0nh ngh\u1ec1, th\u01b0\u1eddng bao gi\u1edd m\u00ecnh c\u0169ng khuy\u00ean h\u00e3y theo \u0111u\u1ed5i nh\u1eefng g\u00ec b\u1ea1n th\u00edch. C\u00f2n trong tr\u01b0\u1eddng h\u1ee3p b\u1ea1n kh\u00f4ng th\u00edch g\u00ec \u0111\u1eb7c bi\u1ec7t h\u1ebft m\u00e0 l\u1ea1i m\u1ea1nh v\u1ec1 c\u00e1c m\u00f4n t\u1ef1 nhi\u00ean, th\u00ec h\u00e3y h\u1ecdc Data Science (DS) \u0111i. V\u00ec sao \u00e0? V\u00ec \u0111\u00e2y l\u00e0 ng\u00e0nh ngh\u1ec1 h\u1ea5p d\u1eabn nh\u1ea5t th\u1ebf k\u1ec9 21 n\u00e0y, \u0111\u01b0\u1ee3c tr\u1ea3 l\u01b0\u01a1ng cao ng\u1ea5t ng\u01b0\u1edfng n\u00e0y (theo Burch Works, 2018: trung b\u00ecnh ~100,000$\/n\u0103m cho junior, link b\u00e0i vi\u1ebft ph\u00eda d\u01b0\u1edbi), v\u00ec th\u1ecb tr\u01b0\u1eddng \u0111ang c\u1ef1c k\u00ec khan hi\u1ebfm l\u01b0\u1ee3ng nh\u00e2n l\u1ef1c n\u00e0y. Nghe giang h\u1ed3 \u0111\u1ed3n th\u1ed5i, c\u00f3 c\u00f4ng ty n\u1ecd \u1edf Vi\u1ec7t Nam s\u0103n l\u00f9ng m\u1ed9t Data Scientist v\u1edbi m\u1ee9c l\u01b0\u01a1ng kh\u1edfi \u0111i\u1ec3m 3000$ m\u00e0 kh\u00f4ng th\u1ec3 t\u00ecm n\u1ed5i \u1ea5y <\/p>\n\n\n\n

\"\"\/<\/figure>\n\n\n\n

;)B\u1ea1n \u0111\u00e3 th\u1ea5y h\u00e0o h\u1ee9ng ch\u01b0a? N\u1ebfu b\u1ea1n mu\u1ed1n bi\u1ebft th\u00eam v\u1ec1 vi\u1ec7c h\u1ecdc DS \u1edf \u0110\u1ee9c th\u00ec xem b\u00e0i vi\u1ebft tr\u01b0\u1edbc c\u1ee7a m\u00ecnh nh\u00e9.C\u00f2n trong b\u00e0i n\u00e0y, th\u1ec3 theo y\u00eau c\u1ea7u c\u1ee7a nhi\u1ec1u b\u1ea1n, m\u00ecnh s\u1ebd cung c\u1ea5p nh\u1eefng t\u00e0i li\u1ec7u m\u00ecnh th\u01b0\u1eddng hay s\u1eed d\u1ee5ng cho vi\u1ec7c t\u1ef1 h\u1ecdc, c\u1ee7ng c\u1ed1 th\u00eam ki\u1ebfn th\u1ee9c tr\u00ean l\u1edbp c\u1ee7a m\u00ecnh.<\/p>\n\n\n\n

I. H\u1ecdc l\u1eadp tr\u00ecnh:M\u1ed9t Data Scientist (DStist) kh\u00f4ng th\u1ec3 kh\u00f4ng bi\u1ebft l\u1eadp tr\u00ecnh, d\u00f9 kh\u00f4ng c\u1ea7n thi\u1ebft ph\u1ea3i gi\u1ecfi nh\u01b0 m\u1ed9t l\u1eadp tr\u00ecnh vi\u00ean nh\u01b0ng ph\u1ea3i \u0111\u1ee7 kh\u1ea3 n\u0103ng vi\u1ebft \u0111\u01b0\u1ee3c nh\u1eefng ch\u01b0\u01a1ng tr\u00ecnh c\u01a1 b\u1ea3n. T\u1eeb khi nh\u1eadp h\u1ecdc t\u1edbi gi\u1edd, t\u1eeb m\u1ed9t \u0111\u1ee9a m\u00e0 ki\u1ebfn th\u1ee9c l\u1eadp tr\u00ecnh l\u00e0 con s\u1ed1 0 tr\u00f2n tr\u00ecnh, m\u00ecnh \u0111\u00e3 h\u1ecdc qua R, Java, Python, SQL (k\u00ec t\u1edbi s\u1ebd c\u00f3 c\u1ea3 NoSQL n\u1eefa). H\u1ecdc t\u1edbi \u0111\u00e2u l\u00e0 s\u1eed d\u1ee5ng lu\u00f4n t\u1edbi \u0111\u1ea5y n\u00ean th\u01b0\u1eddng m\u00ecnh ph\u1ea3i t\u1ef1 h\u1ecdc th\u00eam r\u1ea5t nhi\u1ec1u \u0111\u1ec3 c\u00f3 th\u1ec3 hi\u1ec3u \u0111\u01b0\u1ee3c logic v\u00e0 c\u00fa ph\u00e1p c\u1ee7a ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh \u0111\u00f3. Ng\u00f4n ng\u1eef quan tr\u1ecdng nh\u1ea5t, ph\u1ed5 bi\u1ebfn nh\u1ea5t d\u00e0nh cho DStist l\u00e0 Python v\u1edbi th\u01b0 vi\u1ec7n kh\u1ed5ng l\u1ed3. X\u1ebfp sau Python l\u00e0 R, r\u1ea5t m\u1ea1nh v\u1ec1 ph\u00e2n t\u00edch th\u1ed1ng k\u00ea. N\u0103m ngo\u00e1i m\u00ecnh \u0111\u01b0\u1ee3c Khoa To\u00e1n thu\u00ea vi\u1ebft m\u1ed9t App (ShinyApp) t\u01b0\u01a1ng t\u00e1c d\u00e0nh cho m\u1ed9t d\u1ef1 \u00e1n nghi\u00ean c\u1ee9u c\u1ee7a Bang s\u1eed d\u1ee5ng ng\u00f4n ng\u1eef n\u00e0y.V\u1eady h\u1ecdc l\u1eadp tr\u00ecnh \u1edf \u0111\u00e2u?<\/p>\n\n\n\n

  1. https:\/\/www.tutorialspoint.com\/<\/a><\/li><\/ol>\n\n\n\n

    Trang n\u00e0y th\u00ec gi g\u1ec9 g\u00ec gi c\u00e1i g\u00ec c\u0169ng c\u00f3, th\u00edch h\u1ecdc g\u00ec c\u00f3 ngay c\u00e1i \u0111\u00f3. C\u00f2n nh\u1edb n\u0103m ngo\u00e1i m\u00ecnh c\u1ef1c k\u1ef3 \u0111u\u1ed1i khi c\u00e1c th\u1ea7y b\u1eaft h\u1ecdc th\u00eam Java, v\u1edbi l\u00fd do r\u1eb1ng DStist th\u01b0\u1eddng hay ph\u1ea3i l\u00e0m vi\u1ec7c tr\u1ef1c ti\u1ebfp v\u1edbi l\u1eadp tr\u00ecnh vi\u00ean, v\u1eady th\u00ec ph\u1ea3i h\u1ecdc \u0111\u1ec3 c\u00f3 th\u1ec3 tr\u00f2 chuy\u1ec7n v\u1edbi nhau \u0111\u01b0\u1ee3c. M\u00ecnh \u0111\u00e3 ph\u1ea3i \u0111\u1ecdc th\u00eam s\u00e1ch, \u0111i h\u1ecdc th\u00eam ph\u1ee5 \u0111\u1ea1o, r\u1ed3i l\u1ea1i \u0111\u1ecdc m\u00f2n m\u1ecfi tr\u00ean trang n\u00e0y \u0111\u1ec3 theo k\u1ecbp c\u00e1c b\u1ea1n tr\u00ean l\u1edbp. K\u1ebft qu\u1ea3 l\u00e0 cu\u1ed1i k\u00ec, m\u00ecnh t\u1ef1 vi\u1ebft \u0111\u01b0\u1ee3c c\u1ea3 tr\u00f2 ch\u01a1i v\u00e0 th\u1eadm ch\u00ed c\u00f2n l\u1eadp tr\u00ecnh \u0111\u01b0\u1ee3c c\u00f4ng th\u1ee9c to\u00e1n th\u1ed1ng k\u00ea cho th\u01b0 vi\u1ec7n Java \u0111\u1ea5y.<\/p>\n\n\n\n

    2. https:\/\/codingbat.com\/<\/a>\u0110\u00e2y l\u00e0 n\u01a1i m\u00ecnh luy\u1ec7n vi\u1ebft code, t\u1eeb nh\u1eefng \u1ee9ng d\u1ee5ng \u0111\u01a1n gi\u1ea3n nh\u1ea5t ch\u1ec9 v\u00e0i ba d\u00f2ng. Tr\u00ecnh \u0111\u1ed9 c\u1ee7a m\u00ecnh \u0111\u00e3 l\u00ean r\u1ea5t nhanh sau khi ho\u00e0n th\u00e0nh ph\u00e2n n\u1eeda s\u1ed1 b\u00e0i t\u1eadp tr\u00ean n\u00e0y.<\/p>\n\n\n\n

    3. https:\/\/www.datacamp.com\/<\/a>M\u00ecnh ch\u01b0a s\u1eed d\u1ee5ng trang n\u00e0y bao gi\u1edd, nh\u01b0ng \u0111\u01b0\u1ee3c qu\u1ea3ng c\u00e1o kh\u00e1 nhi\u1ec1u. Tr\u00ean n\u00e0y c\u00f3 c\u00e1c kh\u00f3a h\u1ecdc mi\u1ec5n ph\u00ed R v\u00e0 Python thi\u1ebft k\u1ebf ri\u00eang cho DS. Th\u00edch h\u1ee3p cho nh\u1eefng ai m\u1edbi b\u1eaft \u0111\u1ea7u.<\/p>\n\n\n\n

    4. https:\/\/www.udemy.com\/courses\/development\/programming-languages\/<\/a><\/p>\n\n\n\n

    5. https:\/\/www.codecademy.com\/catalog\/subject\/all<\/a>\u0110\u00e2y l\u00e0 hai trang do b\u1ea1n b\u00e8 m\u00ecnh gi\u1edbi thi\u1ec7u. C\u00f3 m\u1ea5y b\u1ea1n kh\u00f4ng \u0111i h\u1ecdc ph\u1ee5 \u0111\u1ea1o Java \u0111\u01b0\u1ee3c \u0111\u00e3 tr\u1ea3 ti\u1ec1n theo h\u1ecdc tr\u00ean n\u00e0y. V\u00ec th\u01b0\u1eddng xuy\u00ean c\u00f3 gi\u1ea3m gi\u00e1 s\u00e2u n\u00ean kh\u00f3a h\u1ecdc kh\u00f4ng qu\u00e1 \u0111\u1eaft \u0111\u1ecf. V\u00e0 \u0111i\u1ec3m l\u1ee3i th\u1ebf l\u00e0 s\u1ebd c\u00f3 ch\u1ee9ng nh\u1eadn cu\u1ed1i kh\u00f3a, c\u00f3 th\u1ec3 c\u1ee7ng c\u1ed1 th\u00eam cho h\u1ed3 s\u01a1 xin h\u1ecdc ho\u1eb7c xin vi\u1ec7c c\u1ee7a b\u1ea1n.<\/p>\n\n\n\n

    II. H\u1ecdc th\u1ed1ng k\u00ea:\u0110\u00e3 l\u00e0m vi\u1ec7c v\u1edbi d\u1eef li\u1ec7u l\u00e0 ph\u1ea3i hi\u1ec3u l\u00fd thuy\u1ebft th\u1ed1ng k\u00ea, ch\u00ed \u00edt c\u0169ng ph\u1ea3i bi\u1ebft t\u1edbi nh\u1eefng kh\u00e1i ni\u1ec7m c\u01a1 b\u1ea3n nh\u01b0 l\u1ea5y m\u1eabu (sampling), trung b\u00ecnh (mean), trung v\u1ecb (median), \u0111\u1ed9 l\u1ec7ch chu\u1ea9n (standard deviation), h\u1ed3i quy tuy\u1ebfn t\u00ednh (linear regression),… N\u1ebfu mu\u1ed1n tr\u1edf th\u00e0nh DStist th\u00ec c\u00f2n ph\u1ea3i bi\u1ebft t\u1edbi ki\u1ebfn th\u1ee9c th\u1ed1ng k\u00ea n\u00e2ng cao, li\u00ean quan t\u1edbi machine learning. M\u1ed9t \u0111i\u1ec1u tuy\u1ec7t v\u1eddi l\u00e0 nh\u1eefng cu\u1ed1n s\u00e1ch th\u1ed1ng k\u00ea hay ho nh\u1ea5t, t\u1ed5ng h\u1ee3p nh\u1ea5t l\u1ea1i mi\u1ec5n ph\u00ed, nh\u1eb1m \u0111\u00e1p \u1ee9ng nhu c\u1ea7u h\u1ecdc t\u1eadp v\u1ec1 d\u1eef li\u1ec7u ng\u00e0y c\u00e0ng cao. Hai cu\u1ed1n s\u00e1ch m\u00e0 t\u1ea5t c\u1ea3 c\u00e1c gi\u00e1o s\u01b0 Khoa To\u00e1n c\u1ee7a m\u00ecnh \u0111\u1ec1u s\u1eed d\u1ee5ng l\u00e0:<\/p>\n\n\n\n

    1. The Elements of Statistical Learning (Trevor Hastie<\/a>, Robert Tibshirani<\/a>, Jerome H. Friedman<\/a>, 2001)<\/li><\/ol>\n\n\n\n

      Cu\u1ed1n n\u00e0y h\u01a1n 700 trang, chia l\u00e0m 18 ch\u01b0\u01a1ng, s\u1eed d\u1ee5ng R trong ph\u00e2n t\u00edch th\u1ed1ng k\u00ea. B\u1ea3n th\u00e2n m\u00ecnh th\u1ea5y s\u00e1ch qu\u00e1 hay, minh h\u1ecda \u0111\u1ea7y \u0111\u1ee7, gi\u1ea3i th\u00edch k\u0129 c\u00e0ng, \u0111\u1ecdc t\u1edbi \u0111\u00e2u c\u00f3 th\u1ec3 copy code \u0111\u1ebfn \u0111\u1ea5y \u0111\u1ec3 t\u1ef1 th\u1eed nghi\u1ec7m. D\u0129 nhi\u00ean b\u1ea1n kh\u00f4ng c\u1ea7n ph\u1ea3i \u0111\u1ecdc h\u1ebft s\u00e1ch. \u0110\u1ee5ng t\u1edbi kh\u00e1i ni\u1ec7m th\u1ed1ng k\u00ea n\u00e0o th\u00ec tra c\u1ee9u t\u01b0\u01a1ng \u1ee9ng trong s\u00e1ch c\u0169ng \u0111\u01b0\u1ee3c.https:\/\/web.stanford.edu\/~hastie\/Papers\/ESLII.pdf<\/a>2. An Introduction to Statistical Learning: With Applications in R ( Trevor Hastie<\/a>, Robert Tibshirani<\/a>, Daniela Witten<\/a>, Gareth James<\/a>, 2013)Cu\u1ed1n n\u00e0y c\u0169ng hay, h\u01a1n 400 trang, chia l\u00e0m 10 ch\u01b0\u01a1ng, c\u0169ng d\u00f9ng R. Ai ng\u1ea1i \u0111\u1ecdc cu\u1ed1n tr\u00ean th\u00ec c\u00f3 th\u1ec3 b\u1eaft \u0111\u1ea7u v\u1edbi cu\u1ed1n n\u00e0y.https:\/\/www-bcf.usc.edu\/~gareth\/ISL\/ISLR%20First%20Printing.pdf<\/a>III. H\u1ecdc Data Science – N\u00e2ng cao:Sau khi c\u00f3 ch\u00fat ki\u1ebfn th\u1ee9c c\u01a1 b\u1ea3n v\u1ec1 l\u1eadp tr\u00ecnh v\u00e0 th\u1ed1ng k\u00ea r\u1ed3i th\u00ec b\u1ea1n c\u00f3 th\u1ec3 s\u1eed d\u1ee5ng c\u00e1c trang sau \u0111\u1ec3 t\u00ecm hi\u1ec3u th\u00eam v\u1ec1 c\u00e1c m\u1ea3ng ch\u00ednh c\u1ee7a DS nh\u01b0 artificial intelligence, computer vision, machine learning, Big Data Analytics, Business Intelligence…<\/p>\n\n\n\n

      1. https:\/\/towardsdatascience.com\/<\/a><\/li><\/ol>\n\n\n\n

        \u0110\u00e2y l\u00e0 trang t\u1ed5ng h\u1ee3p c\u1ef1c k\u00ec nhi\u1ec1u b\u00e0i vi\u1ebft ch\u1ea5t l\u01b0\u1ee3ng t\u1eeb c\u00e1c gi\u00e1o s\u01b0 v\u00e0 chuy\u00ean gia trong ng\u00e0nh. C\u00f3 r\u1ea5t nhi\u1ec1u b\u00e0i h\u01b0\u1edbng d\u1eabn chi ti\u1ebft t\u1eebng b\u01b0\u1edbc cho tr\u00ecnh \u0111\u1ed9 beginner. M\u00ecnh th\u01b0\u1eddng \u0111\u1ecdc tr\u00ean trang n\u00e0y v\u1ec1 machine learning v\u00e0 artificial intelligence (AI). Kh\u00f4ng ch\u1ec9 c\u00f3 nh\u1eefng ph\u00e2n t\u00edch r\u1ea5t c\u1eb7n k\u1ebd v\u1ec1 m\u1eb7t l\u00fd thuy\u1ebft, nhi\u1ec1u b\u00e0i vi\u1ebft c\u00f2n cung c\u1ea5p v\u00ed d\u1ee5 minh h\u1ecda v\u00e0 \u0111\u00ednh k\u00e8m c\u1ea3 code \u0111\u1ec3 b\u1ea1n \u0111\u1ecdc t\u1ef1 th\u1eed nghi\u1ec7m. V\u00ed d\u1ee5 b\u00e0i vi\u1ebft sau v\u1ec1 Deep Learning l\u00e0 c\u1ee7a m\u1ed9t gi\u00e1o s\u01b0 \u1edf Barcelona, to\u00e0n b\u1ed9 Code c\u00f3 trong Notebook tr\u00ean Google Colab. V\u00ec ch\u1ea1y tr\u00ean Cloud n\u00ean b\u1ea1n kh\u00f4ng c\u1ea7n c\u00e0i \u0111\u1eb7t g\u00ec m\u00e0 c\u00f3 th\u1ec3 l\u1eadp t\u1ee9c ch\u1ea1y ch\u01b0\u01a1ng tr\u00ecnh ngay \u0111\u01b0\u1ee3c, c\u1ef1c k\u00ec ph\u00f9 h\u1ee3p cho nh\u1eefng ai mu\u1ed1n xem qua tr\u01b0\u1edbc v\u00e0 kh\u00f4ng mu\u1ed1n m\u1ea5t c\u00f4ng c\u00e0i \u0111\u1eb7t n\u00e0y n\u1ecd.https:\/\/towardsdatascience.com\/deep-learning-for-beginners-practical-guide-with-python-and-keras-d295bfca4487<\/a><\/p>\n\n\n\n

        2. https:\/\/www.datascienceweekly.org\/<\/a>M\u1ed9t b\u1ea1n ng\u01b0\u1eddi Na Uy tr\u00ean Tandem gi\u1edbi thi\u1ec7u cho m\u00ecnh v\u1ec1 trang n\u00e0y, b\u1ea3o r\u1eb1ng \u0111ang t\u1ef1 h\u1ecdc machine learning \u1edf \u0111\u00e2y. Th\u1ebf l\u00e0 m\u00ecnh c\u0169ng \u0111\u0103ng k\u00fd nh\u1eadn Newsletter t\u1eeb m\u1ea5y h\u00f4m tr\u01b0\u1edbc. M\u1ed7i tu\u1ea7n, m\u00ecnh nh\u1eadn \u0111\u01b0\u1ee3c m\u1ed9t email t\u1ed5ng h\u1ee3p c\u00e1c b\u00e0i vi\u1ebft n\u1ed5i b\u1eadt trong ng\u00e0nh. Nh\u01b0 v\u1eady \u0111\u1ec3 m\u00ecnh lu\u00f4n n\u1eafm b\u1eaft \u0111\u01b0\u1ee3c nh\u1eefng xu h\u01b0\u1edbng m\u1edbi nh\u1ea5t v\u00e0 c\u1eadp nh\u1eadt nh\u1eefng ti\u1ebfn b\u1ed9 c\u00f4ng ngh\u1ec7 m\u1edbi.<\/p>\n\n\n\n

        3. https:\/\/www.kaggle.com\/<\/a>M\u1ed9t \u0111\u1ed3ng nghi\u1ec7p ng\u01b0\u1eddi \u1ea4n \u0110\u1ed9 ch\u1ec9 cho m\u00ecnh trang n\u00e0y qu\u00e1 hay lu\u00f4n. \u0110\u00e2y l\u00e0 n\u01a1i b\u1ea1n h\u1ecdc h\u1ecfi b\u1eb1ng c\u00e1ch th\u1ef1c h\u00e0nh qua c\u00e1c d\u1ef1 \u00e1n, c\u00e1c cu\u1ed9c thi v\u00e0 th\u1eed th\u00e1ch qu\u1ed1c t\u1ebf. C\u00e1c c\u00f4ng ty, t\u1ed5 ch\u1ee9c treo gi\u1ea3i th\u01b0\u1edfng c\u00f3 khi l\u00ean t\u1edbi c\u1ea3 100,000$ cho \u0111\u1ed9i n\u00e0o chi\u1ebfn th\u1eafng. Ch\u1eb3ng h\u1ea1n hi\u1ec7n gi\u1edd c\u00f3 20 cu\u1ed9c thi \u0111\u1ea5u song song, v\u00e0 \u0111\u00e3 c\u00f3 h\u00e0ng ng\u00e0n \u0111\u1ed9i \u0111\u0103ng k\u00ed tham gia. Tr\u00ean n\u00e0y c\u0169ng c\u00f3 c\u00e1c micro-courses ho\u00e0n to\u00e0n mi\u1ec5n ph\u00ed t\u1eeb Python cho t\u1edbi Deep Learning d\u00e0nh cho beginner.https:\/\/www.kaggle.com\/learn\/overview<\/a><\/p>\n\n\n\n

        4. https:\/\/www.coursera.org\/browse\/data-science<\/a><\/p>\n\n\n\n

        V\u00e0 cu\u1ed1i c\u00f9ng, d\u0129 nhi\u00ean l\u00e0 tr\u00ean coursera c\u0169ng c\u00f3 kh\u00f3a h\u1ecdc mi\u1ec5n ph\u00ed d\u00e0nh cho DS. Khi n\u00e0o c\u00f3 th\u1eddi gian, b\u1ea1n th\u1eed \u0111\u0103ng k\u00fd xem sao.Tr\u00ean \u0111\u00e2y l\u00e0 nh\u1eefng h\u01b0\u1edbng d\u1eabn chung d\u00e0nh cho nh\u1eefng ai mu\u1ed1n t\u00ecm hi\u1ec3u v\u1ec1 Data Science v\u00e0 h\u1ecdc nh\u1eefng k\u0129 n\u0103ng c\u01a1 b\u1ea3n tr\u01b0\u1edbc. Hi v\u1ecdng gi\u00fap \u0111\u01b0\u1ee3c c\u00e1c b\u1ea1n \u0111ang quan t\u00e2m. M\u00ecnh s\u1ebd ti\u1ebfp t\u1ee5c c\u1eadp nh\u1eadt th\u00eam nh\u00e9.Blog Mai Knowshttps:\/\/www.facebook.com\/maiknowsnow\/<\/a>
        Link tham kh\u1ea3o v\u1ec1 l\u01b0\u01a1ng c\u1ee7a DStist:<\/em>        https:\/\/www.burtchworks.com\/2018\/07\/09\/2018-data-scientist-salary-report-highlights\/<\/a>Ngu\u1ed3n \u1ea3nh:<\/em>https:\/\/www.datanami.com\/2018\/09\/17\/improving-your-odds-with-data-science-hiring\/<\/em><\/a><\/p>\n\n\n\n

        by Mai Tr\u1ea7n<\/p>\n","protected":false},"excerpt":{"rendered":"

        Nhi\u1ec1u b\u1ea1n nh\u1eafn tin h\u1ecfi m\u00ecnh v\u1ec1 vi\u1ec7c ch\u1ecdn ng\u00e0nh ngh\u1ec1, th\u01b0\u1eddng bao gi\u1edd m\u00ecnh c\u0169ng khuy\u00ean h\u00e3y theo \u0111u\u1ed5i […]<\/p>\n","protected":false},"author":2,"featured_media":384,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[131,94,111],"tags":[139,137,138],"class_list":["post-383","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kiem-tien-bitcoin","category-tin-giai-tri","category-tin-tuc-4-0","tag-data-scientist","tag-ky-su-may-tinh","tag-luong"],"_links":{"self":[{"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/posts\/383","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/comments?post=383"}],"version-history":[{"count":2,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/posts\/383\/revisions"}],"predecessor-version":[{"id":389,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/posts\/383\/revisions\/389"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/media\/384"}],"wp:attachment":[{"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/media?parent=383"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/categories?post=383"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cafe2sach.com\/index.php\/wp-json\/wp\/v2\/tags?post=383"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}