資料科學
No great marketing decisions have ever been made on qualitative data.
— John Sculley, ex-CEO of Apple
◎ 所有的科學都是資料科學！
由於人工智慧決策都必須建立在龐大的資料量之上，台灣資料科學協會理事長陳昇瑋就曾說：未來所有的工具都會是大數據，而資料科學是不會消失的。
◎ 想成為一名資料科學家嗎？可不是這麼容易！
資料科學覆蓋的面向相當的廣泛，至少需要一個團隊才能完整地覆蓋整個領域：擅長數學統計的數據科學家(Data Scientist) 、精通撰寫程式的數據工程師(Data Engineer) 、以及呈現視覺化圖表的視覺設計師(Visual Designer)，更不用說還需要其應用領域的專業人員監督與諮詢。
◎ 從新手入門到數據應用其實也沒那麼困難～
正如所有的科學一般，資料科學也是從觀察資料、提出假設、驗證結果一步步實現模型優化與最佳化。
資料科學涵蓋太過廣泛...不如就先從其中一個領域開始專精吧！
想從基本的統計、機率扎根；或是直接切入R、Python程式起手無痛學習；商業應用、行銷分析、視覺化或資料庫......
以下書單都可是應有盡有！
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