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What are some skills needed to get into Data Science or Statistical Analysis

There is not substantial information out there for free on what it takes to start studying Statistical Analysis. Looking for what books to read that give a thorough understanding of the basics or a outline of the whole process. #finance #programming #data-science #data-analysis #data-mining #personal-development

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Debashri’s Answer

Hi Mihai! Data Science can seem like a daunting avenue- there's so much to learn and so many subjects to explore. While that's true, there's also a lot of free information scattered throughout the internet. To help you in this search, here's a resource that I found very useful when I was in the same position that you are in right now- (https://trello.com/b/rbpEfMld/data-science). It's an amazing Trello board full of links to content that will give you more than a head start into your foray of data science. Good luck! :)
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Natalie’s Answer

Hello MIhai,


Quantitative, research, technology and analytical skills are crucial to be successful in this field. You don't have to major specifically in Data Sciences or Statistical Analysis. The most popular majors of people who currently work in this field are statistics (actuarial science) or computer science but it is important to have a foundation in both areas. I hope this helps.


Good Luck!


Natalie

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Nick’s Answer

Mihai,


Data Science typically straddles the area between software engineering and statistics, so some skills are necessary from both. Obviously, a solid foundation of basic statistics is necessary, and to start I would augment that with coding ability in Python. Learning a more stats-oriented tool such as R or SPSS can also be helpful.
Here's a short overview on StackExchange (http://stats.stackexchange.com/questions/195034/what-is-a-data-scientist) which includes an illustrative diagram also found here (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram). Hope this helps!

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Sofia’s Answer

Hey Mihai,

For data science, a great way to start is by learning Python. There is a great course (for $15) available on Udemy https://www.udemy.com/course/python-django-programming-beginner-to-advance-tutorial-step-by-step/. This is great to start off with. Throughout the course you will hear new concepts that will make the data science route more clear to you.

You can also download the app "Shapr" that allows you to network with other business professionals who can also answer your questions regularly.

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Steve’s Answer

You need to love numbers and data. The world is full of data and each day more and more gets collected. SQL stands for Structured Query Language and it is very useful for extracting data out of databases to use in statistical analysis. There are so many tools out there that are evolving daily that can be used by Data Scientists. Google has a whole suite of products for Data Science. YouTube is great resource for free videos to learn more about Data Science.

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Chris’s Answer

Hi Mihai,


That's a great question! A data scientist often does many different things, using statistics or programming. If you're starting out, it can be useful to get a feeling for the great work that others have done. You can then look at what you find interesting and learn the skills. That's how I started out in data science - I knew that a lot of my friends had fun projects, and I wanted to do what they were doing!


For instance, here is a huge list of projects: https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks. Do these look interesting to you?


For instance, this project (http://nbviewer.jupyter.org/url/www.asimihsan.com/articles/Intro%20to%20Data%20Science%20-%20Final%20Project.ipynb) is looking at when people use the subway in New York City. That person is using a lot of coding and graphing to make sense of the data. Then they do more complicated statistics. And that's a good example of what the work could look like.

Chris recommends the following next steps:

Look at the list of notebooks
Pick the project that you find most interesting
Summarize the project
What would you look at that the project hasn't done?
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