零经验如何成为数据科学家?

{"type":"doc","content":[{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"成为一名数据科学家不再是空想了。本文是帮助你成为数据科学家的“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":"人们都希望自己具有先见之明,能够选择完美的职业,并为之做好必要的准备,但是现实生活中的道路并不总是直线式的,这也是人生乐趣所在。"}]},{"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":"随着科技飞速发展,不断涌现出许多新兴行业。数据科学就是一个高增长、高需求、有良好工作前景的行业。值得庆幸的是,成为一个数据科学家并不需要具备一定的工作经验。换句话说,哪怕你零经验,也可以通过多种方式获取数据科学技能,从而成为数据科学家。"}]},{"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":"不过在探索如何零经验成为数据科学家之前,我们先来定义一下数据科学家究竟是干什么的。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"什么是数据科学家"}]},{"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":"数据科学家收集和清理大量的数据,维护易于使用的仪表板和数据库,解释数据以解决问题和运行实验,建立算法,并以吸引人的可视化方式将数据呈现给利益相关者。"}]},{"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":"数据科学家这一职业有很多优势,比如高薪,即使是在全球经济衰退时期,也保持相对稳定和不断增长的就业市场。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"数据科学难吗?"}]},{"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":"数据科学是否难,其实取决于你的背景以及你是否喜欢与数字、数据打交道。尽管数据科学家不需要像数据工程师那样使用软件工程或者机器学习技术,但是你需要学习如何编写代码来建立预测模型。"}]},{"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,数据科学的学习曲线非常陡峭,它涉及棘手的问题、大量的数据、专业技术和领域知识。但是幸运的是,有很多免费的在线资源可以帮助你开始成为一名初级数据科学家。最后,你还要热爱学习,因为数据科学家需要不断提高技能,学习新技术。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"成为数据科学家需要学位吗?"}]},{"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":"学习数据科学不需要高等学历,尽管大部分招聘信息列出了工程学、计算机科学、数学或统计学硕士或博士学位,但对数据科学家的需求量远远大于供应量,这意味着企业愿意雇佣非传统的申请者。实际上,很多顶级公司,比如谷歌,苹果和 IBM,都不再要求申请者具有大学学历。"}]},{"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":"如果你想在没有学位的情况下进入数据科学领域,你可以参加在线课程和认证项目,或者通过视频和模块自学。"}]},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"成为数据科学家的六个步骤"}]},{"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":"下面这的六个步骤可以帮助你零经验就能进入数据科学领域。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤一、提高数学技能"}]},{"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,那么应该很容易学习数据科学。使用高科技工具进行数据分析前,首先要掌握数据分析的基本方法,沿着 X 轴和 Y 轴在图表上绘制数据点,并找到不同变量之间的相关性和趋势。"}]},{"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":"为了确保你能写出高效的代码并得出准确的结论,以下是一些需要掌握的数学概念:"}]},{"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":"统计方法与概率论"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"概率分布"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"线性代数"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"假设检定"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"统计建模与拟合"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"数据摘要与描述性统计"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"回归分析"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"贝叶斯思维与建模"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"马尔科夫链"}]}]}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤二、学习一门编程语言(或两门)"}]},{"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":"相对于其它职业领域,数据科学更在意的是你所知道的东西,以及你的相关技能,而非母校的声誉。以技能为基础的面试过程往往会给来自不同背景的人一个公平的机会。"}]},{"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":"只要有了坚实的数学基础,你就可以开始学习 SQL、R、Python 和 SAS 这几种数据科学家需要掌握的编程语言。下面简单介绍下这些语言:"}]},{"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 是一种脚本语言,它的库可以让你整理、过滤和转换大数据和非结构化数据。Python可用于网络开发、软件开发、深度学习和机器学习。它是数据科学家最经常使用的工具。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"R 是一种开源编程语言,可用于复杂的数学和统计计算。同时,它也提供了数据可视化功能,还有一个庞大的支持社区来帮助你开始入门。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"SQL 是一种关系管理工具,通过它可以查询和连接多个表和数据库的数据。"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"SAS 是一种昂贵的工具,被大公司用于统计分析、商业智能和预测分析,但由于成本原因,不推荐个人使用。如果你学会了其他语言,你就能轻松地在工作中掌握 SAS。"}]}]}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤三、参加业余项目或实习"}]},{"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":"当你开始建立你的知识库时,你可以将自己的技能组合应用于现实世界,并获得实时反馈。比如,你可以使用像 Upwork 或 Fiverr 这样的自由职业平台,或者通过社交媒体和招聘网站寻找兼职工作或实习的机会。"}]},{"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,在参加面试之前,一定要在 LeetCode 上练习解决编码问题,并探索潜在的数据科学面试问题。你也可以将自己以往的作品展示在 GitHub、LinkedIn 或者个人网站上,以建立一个良好的投资组合和强大的网络形象。"}]},{"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":"通过利用在线社区,你也可以证明你有能力把数据科学知识转化成可衡量的商业结果。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤四、从数据分析师开始"}]},{"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":"数据科学家和数据分析师是两个不同的职业,但相同点是他们都在爆炸性增长。"}]},{"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":"数据分析师管理数据收集并确定数据集趋势。数据科学家不仅要解释数据,还要运用编码与数学建模的技巧。"}]},{"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":"如果你未来想成为数据科学家的话,那么最好把数据分析员当作你的起点,因为这个职位相对来说更容易应聘成功。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤五、勤奋工作,努力拓展人脉"}]},{"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":"结识其他数据科学家是了解不同职业机会的最佳途径,这个过程甚至还能遇到你未来的团队成员。此外,你也可以通过拓展人脉,发现自己想要在哪一家公司工作(规模、行业、文化),自己喜欢什么项目,以及怎样为求职做准备。"}]},{"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":"在起步阶段,缺乏经验的求职者可能更容易进入小公司,而那些在科技行业有初级项目的大公司,则可能有更多的内部培训和指导基础设施。"}]},{"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":"还有一种选择是从公司的其他职位转到数据科学。假如你有很好的声誉,你就可以开始在公司内部建立联系,并且寻找机会去参加一个数据科学小组的面试。"}]},{"type":"heading","attrs":{"align":null,"level":3},"content":[{"type":"text","text":"步骤六、向潜在雇主解释职业转型"}]},{"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":"数据科学是一个高度交叉的学科领域,并需要将模型与直接的业务影响联系起来。在简历和求职信中,你一定要着重于自己在数据科学方面的工作经历,同时你也要提到自己过去使用微软 Excel 或开发业务、沟通、协作和其他可转移技能的角色。"}]},{"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":"应聘无经验的数据科学工作时,请在简历中附上一个简短的总结部分,以说明你的转型,并列出你所学的课程、技术语言,以及当前掌握的数据科学领域技能。"}]},{"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":"原文链接:"}]},{"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\/"}]}]}
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