零經驗如何成爲數據科學家？

{"type":"doc","content":[{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"成爲一名數據科學家不再是空想了。本文是幫助你成爲數據科學家的“小抄”。"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"人們都希望自己具有先見之明，能夠選擇完美的職業，併爲之做好必要的準備，但是現實生活中的道路並不總是直線式的，這也是人生樂趣所在。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"隨着科技飛速發展，不斷湧現出許多新興行業。數據科學就是一個高增長、高需求、有良好工作前景的行業。值得慶幸的是，成爲一個數據科學家並不需要具備一定的工作經驗。換句話說，哪怕你零經驗，也可以通過多種方式獲取數據科學技能，從而成爲數據科學家。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"不過在探索如何零經驗成爲數據科學家之前，我們先來定義一下數據科學家究竟是幹什麼的。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"什麼是數據科學家"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學家收集和清理大量的數據，維護易於使用的儀表板和數據庫，解釋數據以解決問題和運行實驗，建立算法，並以吸引人的可視化方式將數據呈現給利益相關者。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學家這一職業有很多優勢，比如高薪，即使是在全球經濟衰退時期，也保持相對穩定和不斷增長的就業市場。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"數據科學難嗎？"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學是否難，其實取決於你的背景以及你是否喜歡與數字、數據打交道。儘管數據科學家不需要像數據工程師那樣使用軟件工程或者機器學習技術，但是你需要學習如何編寫代碼來建立預測模型。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"此外，數據科學的學習曲線非常陡峭，它涉及棘手的問題、大量的數據、專業技術和領域知識。但是幸運的是，有很多免費的在線資源可以幫助你開始成爲一名初級數據科學家。最後，你還要熱愛學習，因爲數據科學家需要不斷提高技能，學習新技術。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"成爲數據科學家需要學位嗎？"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"學習數據科學不需要高等學歷，儘管大部分招聘信息列出了工程學、計算機科學、數學或統計學碩士或博士學位，但對數據科學家的需求量遠遠大於供應量，這意味着企業願意僱傭非傳統的申請者。實際上，很多頂級公司，比如谷歌，蘋果和 IBM，都不再要求申請者具有大學學歷。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"如果你想在沒有學位的情況下進入數據科學領域，你可以參加在線課程和認證項目，或者通過視頻和模塊自學。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"成爲數據科學家的六個步驟"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"下面這的六個步驟可以幫助你零經驗就能進入數據科學領域。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟一、提高數學技能"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"假如你有量化背景，那麼應該很容易學習數據科學。使用高科技工具進行數據分析前，首先要掌握數據分析的基本方法，沿着 X 軸和 Y 軸在圖表上繪製數據點，並找到不同變量之間的相關性和趨勢。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"爲了確保你能寫出高效的代碼並得出準確的結論，以下是一些需要掌握的數學概念："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"統計方法與概率論"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"概率分佈"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"線性代數"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"假設檢定"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"統計建模與擬合"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據摘要與描述性統計"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"迴歸分析"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"貝葉斯思維與建模"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"馬爾科夫鏈"}]}]}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟二、學習一門編程語言（或兩門）"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"相對於其它職業領域，數據科學更在意的是你所知道的東西，以及你的相關技能，而非母校的聲譽。以技能爲基礎的面試過程往往會給來自不同背景的人一個公平的機會。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"只要有了堅實的數學基礎，你就可以開始學習 SQL、R、Python 和 SAS 這幾種數據科學家需要掌握的編程語言。下面簡單介紹下這些語言："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"Python 是一種腳本語言，它的庫可以讓你整理、過濾和轉換大數據和非結構化數據。Python可用於網絡開發、軟件開發、深度學習和機器學習。它是數據科學家最經常使用的工具。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"R 是一種開源編程語言，可用於複雜的數學和統計計算。同時，它也提供了數據可視化功能，還有一個龐大的支持社區來幫助你開始入門。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"SQL 是一種關係管理工具，通過它可以查詢和連接多個表和數據庫的數據。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"SAS 是一種昂貴的工具，被大公司用於統計分析、商業智能和預測分析，但由於成本原因，不推薦個人使用。如果你學會了其他語言，你就能輕鬆地在工作中掌握 SAS。"}]}]}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟三、參加業餘項目或實習"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"當你開始建立你的知識庫時，你可以將自己的技能組合應用於現實世界，並獲得實時反饋。比如，你可以使用像 Upwork 或 Fiverr 這樣的自由職業平臺，或者通過社交媒體和招聘網站尋找兼職工作或實習的機會。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"此外，在參加面試之前，一定要在 LeetCode 上練習解決編碼問題，並探索潛在的數據科學麪試問題。你也可以將自己以往的作品展示在 GitHub、LinkedIn 或者個人網站上，以建立一個良好的投資組合和強大的網絡形象。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"通過利用在線社區，你也可以證明你有能力把數據科學知識轉化成可衡量的商業結果。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟四、從數據分析師開始"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學家和數據分析師是兩個不同的職業，但相同點是他們都在爆炸性增長。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據分析師管理數據收集並確定數據集趨勢。數據科學家不僅要解釋數據，還要運用編碼與數學建模的技巧。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"如果你未來想成爲數據科學家的話，那麼最好把數據分析員當作你的起點，因爲這個職位相對來說更容易應聘成功。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟五、勤奮工作，努力拓展人脈"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"結識其他數據科學家是瞭解不同職業機會的最佳途徑，這個過程甚至還能遇到你未來的團隊成員。此外，你也可以通過拓展人脈，發現自己想要在哪一家公司工作（規模、行業、文化），自己喜歡什麼項目，以及怎樣爲求職做準備。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"在起步階段，缺乏經驗的求職者可能更容易進入小公司，而那些在科技行業有初級項目的大公司，則可能有更多的內部培訓和指導基礎設施。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"還有一種選擇是從公司的其他職位轉到數據科學。假如你有很好的聲譽，你就可以開始在公司內部建立聯繫，並且尋找機會去參加一個數據科學小組的面試。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步驟六、向潛在僱主解釋職業轉型"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"數據科學是一個高度交叉的學科領域，並需要將模型與直接的業務影響聯繫起來。在簡歷和求職信中，你一定要着重於自己在數據科學方面的工作經歷，同時你也要提到自己過去使用微軟 Excel 或開發業務、溝通、協作和其他可轉移技能的角色。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"應聘無經驗的數據科學工作時，請在簡歷中附上一個簡短的總結部分，以說明你的轉型，並列出你所學的課程、技術語言，以及當前掌握的數據科學領域技能。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"原文鏈接："}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"https:\/\/www.springboard.com\/library\/data-science\/how-to-become-without-experience\/"}]}]}