【转载】如何成为一个数据科学家：Becoming a Data Scientist – Curriculum via Metr

最近看到一张图，road to data scientist:
附链接：http://nirvacana.com/thoughts/becoming-a-data-scientist/

全文：

Becoming a Data Scientist – Curriculum via Metromap
8 Jul 2013 by Swami Chandrasekaran


. 1point3acres.com

Data Science, Machine Learning, Big Data Analytics, Cognitive Computing …. well all of us have been avalanched with articles, skills demand info graph’s and point of views on these topics (yawn!). One thing is for sure; you cannot become a data scientist overnight. Its a journey, for sure a challenging one. But how do you go about becoming one? Where to start? When do you start seeing light at the end of the tunnel? What is the learning roadmap? What tools and techniques do I need to know? How will you know when you have achieved your goal?

Given how critical visualization is for data science, ironically I was not able to find (except for a few), pragmatic and yet visual representation of what it takes to become a data scientist. So here is my modest attempt at creating a curriculum, a learning plan that one can use in this becoming a data scientist journey. I took inspiration from the metro maps and used it to depict the learning path. I organized the overall plan progressively into the following areas / domains,

• Fundamentals
• Statistics
• Programming
• Machine Learning
• Text Mining / Natural Language Processing
• Data Visualization
• Big Data
• Data Ingestion
• Data Munging
• Toolbox
  

Each area  / domain is represented as a “metro line”, with the stations depicting the topics you must learn / master / understand in a progressive fashion. The idea is you pick a line, catch a train and go thru all the stations (topics) till you reach the final destination (or) switch to the next line. I have progressively marked each station (line) 1 thru 10 to indicate the order in which you travel. You can use this as an individual learning plan to identify the areas you most want to develop and the acquire skills. By no means this is the end; but a solid start. Feel free to leave your comments and constructive feedback.

PS: I did not want to impose the use of any commercial tools in this plan. I have based this plan on tools/libraries available as open source for the most part. If you have access to a commercial software such as IBM SPSS or SAS Enterprise Miner, by all means go for it. The plan still holds good.

PS: I originally wanted to create an interactive visualization using D3.js or InfoVis. But wanted to get this out quickly. Maybe I will do an interactive map in the next iteration.

good stuff！

虽然我不知道你们说什么,不过看起来很厉害的样子

这图好厉害....但是我越来越困惑了

粮果 发表于 2013-12-29 20:04
这图好厉害....但是我越来越困惑了

困惑什么？

很清晰，和doing data science这本书基本一致，但要涉及的面太广了，还在努力学习中。

很强大！ 不过就是感觉侧重有不同。做text mining的跟做统计的基本不是对着同一种职业的样子。。。。

刚发现，居然有我学的spark。。

VERY GOOD!

这个图好强大，楼主已经修炼出来了？