字幕表 動画を再生する 英語字幕をプリント - My advice to an aspiring data scientist is to be curious, extremely argumentative, judgmental. Curiosity is absolutely must. If you're not curious, you would not know what to do with the data. Judgmental because if you do not have preconceived notions about things, you wouldn't know where to begin. Argumentative because if you can argue then you can plead a case, at least you can start somewhere. And then you learn from data and then you modify your assumptions and hypothesis, and your data would help you learn. And you may start at the wrong point, you may say that I thought I believed this but now with data I know this, so this allows you a learning process. So curiosity, being able to take a position, strong position, and then moving forward with it. The other thing that a data scientist would need is some comfort and flexibility with analytics platforms. Some software, some computing platform but that's secondary. The most important thing is curiosity and the ability to take positions. Once you have done that, once you've analyzed, then you've got some answers. And that's the last thing that a data scientist needs and that is the ability to tell a story. That once you have your analytics, once you have your tabulations, now you should be able to tell a great story from it. Because if you don't tell a great story from it, your findings will remain hidden, it will remain buried, nobody would know, but your rise to prominence is pretty much relying on your ability to tell great stories. A starting point would be to see what is your competitive advantage? Do you want to be a data scientist in any field or a specific field because let's say you want to be a data scientist and work for an IT firm or a web-based or internet-based firm. Then you need a different set of skills. And if you want to be a data scientist for let's say in the health industry, then you need different sets of skills. So figure out first what your interest is and what is your competitive advantage. Your competitive advantage is not necessarily going to be your analytical skills. Your competitive advantage is your understanding of some aspect of life where you exceed beyond others in understanding that. Maybe it's film, maybe it's retail, maybe it's health, maybe it's computers. Once you have figured out where your expertise lies, then you start acquiring analytical skills, what platforms to learn. And those platforms, those tools would be specific to the industry that you're interested in. And then once you have got some proficiency in the tools, the next thing would be to apply your skills to real problems and then tell rest of the world what you can do with it.
B1 中級 新米データサイエンティストへのアドバイス【データサイエンス101 (Any advice for new data scientist [Data Science 101]) 74 13 陳賢原 に公開 2021 年 01 月 14 日 シェア シェア 保存 報告 動画の中の単語