sql 12天內的數據

重點 (Top highlight)

I see many ads that claim to make you a data scientist in 12 weeks. They say they can teach you Python programming, python libraries like Pandas, Matplotlib, and scikit-learn, another visualization tool like Tableau, SQL, and probably more. After 12 weeks, you will get a job that will earn you about 100,000 USD. But before that, you have to pay a good amount to take those classes. How realistic they are?

我看到許多廣告聲稱可以在12周內使您成為數據科學家。 他們說他們可以教您Python編程，Pandas，Matplotlib等python庫和scikit-learn，Tableau，SQL等其他可視化工具。 12周后，您將獲得一份可為您賺取約100,000美元的工作。 但在此之前，您必須支付大量費用才能參加這些課程。 它們有多現實？

他們現實嗎？ (Are They Realistic?)

It depends on which level you are in. If you already know a programming language and switch to Python for a new career, then you can learn all this in three months if you work hard. But if you do not have any programming background, then it will be too ambitious to think that you can learn all this in three months even if you do not have another job and you focus only on study.

這取決于您所處的級別。如果您已經知道一種編程語言并轉而使用Python從事新的職業，那么如果您努力工作，則可以在三個月內學到所有這一切。 但是，如果您沒有任何編程背景，那么即使您沒有其他工作并且只專注于學習，也很難想到您可以在三個月內學會所有這些知識。

合理的時間表 (A Reasonable TimeFrame)

If you want to become a data scientist, you need to learn at least one of these two languages. And learning programming languages does not mean just learning if/else statement and loops. It is more than that. You need to learn the data structures and programming problem-solving which takes some time. You should dedicate at least three months to learn a language only. If you do not and rush into learning libraries, databases all at once, you may end up learning everything to an extent that it will not be useful. I am not saying you need to be an absolute expert in programming before you can start learning anything else. But you need to be at least comfortable writing some code solving problems. There are a lot of programming problems out there to test yourself. I suggest, try leetcode. They have three different categories of problems in leetcode, easy, medium, and hard. See if you can solve some easy problems. Then move on to learn the libraries like Numpy, Pandas, Matplotlib, seaborn, scikit-learn, and others.

如果您想成為數據科學家，則需要至少學習這兩種語言中的一種。 學習編程語言并不意味著只學習if / else語句和循環。 不僅如此。 您需要學習數據結構和編程問題解決，這需要一些時間。 您應該花至少三個月的時間只學習一種語言。 如果您不這樣做而立即進入所有的學習庫和數據庫，那么您可能最終會學到一切都將無用的程度。 我并不是說您需要成為編程方面的絕對專家，然后才能開始學習其他內容。 但是您至少需要習慣于編寫一些解決問題的代碼。 有很多編程問題可以測試自己。 我建議嘗試使用leetcode 。 他們在leetcode中有三類不同的問題，簡單，中等和困難。 看看是否可以解決一些簡單的問題。 然后繼續學習Numpy，Pandas，Matplotlib，seaborn，scikit-learn等庫。

Learning just a few of those libraries should take another three months. It takes some time to practice and grasp the ideas of Exploratory Data Analysis and do it yourself. Learning SQL should not take too much time because you will find lots of similarities between Pandas and SQL. But still, even if you learn fast, learning to use several big datasets and intermediate level complex queries, organizing and setting up datasets will be a couple of months. So, I am talking about at least eight months.

僅學習其中一些圖書館還需要三個月的時間。 練習和掌握探索性數據分析的想法并自行完成需要一些時間。 學習SQL不需要花費太多時間，因為您會發現Pandas和SQL之間有很多相似之處。 但是，即使您學得很快，學會使用多個大型數據集和中級復雜查詢，組織和設置數據集也要花費幾個月的時間。 因此，我至少要談論八個月。

這些只是最低要求 (These Are Just The Minimum)

If you have good contacts and you are lucky enough, you will find a job after that. But you need to keep in mind that you have to keep learning more tools. More concepts. You need to keep improving your programming skills. One important thing is statistics. If you are already good at it, great! Otherwise, at least learn some beginner level inferential statistics and model fitting and learn to implement them in Python or R. Python’s scikit-learn library is just a tool for machine learning. But learning some genuine concepts will be useful. Also, I see Data Mining as an important skill. There is so much data out there. We need to extract them. Lots of job opening ask for it as well.

如果您有良好的聯系并且很幸運，那么您將找到一份工作。 但是您需要記住，您必須繼續學習更多工具。 更多概念。 您需要不斷提高自己的編程技能。 重要的一件事是統計。 如果您已經很擅長，那就太好了！ 否則，至少要學習一些初學者的推理統計數據和模型擬合，并學習在Python或R中實現它們。Python的scikit-learn庫只是用于機器學習的工具。 但是學習一些真正的概念將是有用的。 另外，我將數據挖掘視為一項重要技能。 那里有很多數據。 我們需要提取它們。 許多職位空缺也要求它。

I do not want to be discouraging. If you can develop all those skills, you will be in demand in the job market. So, spending a year or two is not a bad idea at all. It will add so much value to your life.

我不想氣disc。 如果您能開發所有這些技能，那么就業市場將是您的需求。 因此，花費一兩年根本不是一個壞主意。 它會為您的生活增添很多價值。

12周到18周的合理時間 (What Is Reasonable In 12 Weeks To 18 Weeks)

It looks too tough to become a data scientist in 12 weeks. But if you do not have that much time and want to get a job soon, probably becoming a Data Analyst will be a decent goal. If you are a college graduate or a college student, I am sure, you know excel.

看起來很難在12周內成為一名數據科學家。 但是，如果您沒有那么多時間并且想盡快找到工作，那么成為數據分析師可能是一個不錯的目標。 如果您是大學畢業生或大學生，我相信您會知道。

Polish your excel skills some more. Learn some advanced techniques like v-lookup, pivot table, Macros, visual basic. I think it will be faster to pick up for you. Excel is so advanced right now. There are a lot of data analyst roles that want advanced excel skills.

進一步提高您的Excel技能。 了解一些高級技術，例如v查找，數據透視表，宏，Visual Basic。 我認為接您的速度會更快。 Excel現在是如此先進。 有許多數據分析師角色需要高級excel技能。

Learn a good data visualization tool like Tableau. You can do quite a lot of visualization without writing any programming logic or any code. It has so many in-built options. Simple drag and drop can make complex visualizations.

了解像Tableau這樣的優質數據可視化工具。 您無需編寫任何編程邏輯或任何代碼即可進行大量可視化。 它具有許多內置選項。 簡單的拖放可以使復雜的可視化成為可能。

Learn SQL. Learning SQL can be easier than learning a programming language. SQL queries are like regular language. So it’s easier to grasp. Plus it is an invaluable skill in the job market. I meet so many people in different conferences who are working as SQL developers for the last 10 years.

學習SQL 。 學習SQL比學習編程語言更容易。 SQL查詢就像常規語言一樣。 因此更容易掌握。 另外，它是就業市場中的一項寶貴技能。 在過去的十年中，我在不同的會議上遇到了很多人，他們都是SQL開發人員。

Start learning a programming language like Python or R. But you have to keep practicing it for a while to learn it well if this is your first language.

開始學習像Python或R這樣的編程語言。但是，如果這是您的第一門語言，則必須繼續練習一段時間才能很好地學習它。

發展軟技能 (Develop Soft Skills)

These three skills together should make you employable. But we focus too much on learning the tools but we forget to spend some time on developing soft skills.

這三項技能加在一起就可以使您就業。 但是我們過于專注于學習工具，卻忘記花一些時間來開發軟技能。

It is important to develop some business insights where you will use those tools. Without some good real-world knowledge, it will be hard to use those tools effectively. So, read articles, books, or newspapers to stay updated and develop some real-world knowledge. So, you can talk about how to use those tools in a crowd or an interview.

開發一些業務見解以使用這些工具很重要。 沒有一些實際的良好知識，將很難有效地使用這些工具。 因此，請閱讀文章，書籍或報紙以保持更新并發展一些現實世界的知識。 因此，您可以討論如何在人群或訪談中使用這些工具。

Networking is another valuable skill. Attend meetups, go to seminars, conferences, listen to experienced people talk. That’s a good way to develop knowledge and also make contacts.

聯網是另一項寶貴的技能。 參加聚會，參加研討會，會議，聽取經驗豐富的人的講話。 這是發展知識并建立聯系的好方法。

Engage with the community in Stack Overflow, Stack Exchange, and Slack Channels. That will keep you updated about the job market, recent technologies, and improve your soft skills.

與社區一起參與Stack Overflow，Stack Exchange和Slack Channels。 這樣可以使您隨時了解就業市場，最新技術并提高您的軟技能。

結論 (Conclusion)

I am not against Bootcamps. I started my journey with a Bootcamp and I am grateful to that Bootcamp. But it was a six months long Bootcamp to learn programming concepts and SQL only which was realistic. We learned the basics of a few programming languages. More importantly, it was free. It was from LaunchCode. If you are in the US, please check. They are good. I am sure they are still free. My suggestion is, start taking free courses. It is even not necessary at all to pay for learning programming languages. There are a lot of great free courses out there. Coursera, edx, udacity have some good quality free courses. Try some of those free courses first. That will give you some insights. Probably, you will make better decisions about which boot camps to pay your or your parents’ hard-earned money. Otherwise, you might end up becoming another victim. Here is an article I wrote that gives you some free courses links:

我不反對訓練營。 我從一個Bootcamp開始了我的旅程，并對該Bootcamp表示感謝。 但是，只有六個月的Bootcamp學習編程概念和SQL才是現實的。 我們學習了一些編程語言的基礎。 更重要的是，它是免費的。 它來自LaunchCode。 如果您在美國，請檢查。 他們很好。 我相信他們仍然有空。 我的建議是，開始學習免費課程。 甚至根本不需要為學習編程語言付費。 這里有很多很棒的免費課程。 Coursera ， edx ， udacity有一些高質量的免費課程。 首先嘗試一些免費課程。 這將為您提供一些見解。 也許，您將更好地決定要向哪個新兵訓練營支付您或您父母的血汗錢。 否則，您可能最終成為另一個受害者。 這是我寫的一篇文章，為您提供一些免費的課程鏈接：

Recommended Reading:

推薦讀物：

翻譯自: https://towardsdatascience.com/want-to-become-a-data-scientist-in-12-weeks-3926d8eacee2

sql 12天內的數據

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