Three facts you need to realize about data science:
1. Learning is not enough
2. You need experience to get a job
3. You need principles for working
#datascience #66daysofdata
1. Learning is not enough
2. You need experience to get a job
3. You need principles for working
#datascience #66daysofdata
1/ Learning is not enough
A hiring manager isn’t going to be able to open your head, peek inside your brain, and verify if you know how to do this thing or that, or how well you understand this, that or the other.
That’s why you need to do a project.
A hiring manager isn’t going to be able to open your head, peek inside your brain, and verify if you know how to do this thing or that, or how well you understand this, that or the other.
That’s why you need to do a project.
2/ You need experience to get a job
But that doesn’t mean you need a job to get experience.
Data is everywhere.
You don’t need to be in a job at a company to get access to data.
If you know where to look and how to search for it, you’ll quickly see that it is everywhere.
But that doesn’t mean you need a job to get experience.
Data is everywhere.
You don’t need to be in a job at a company to get access to data.
If you know where to look and how to search for it, you’ll quickly see that it is everywhere.
3/ You need principles for working
The data science life cycle is a set of principles for doing data science work.
All problems are different, but you can still use a set of principles to help you find a solution.
You can develop and cultivate this intuition through projects.
The data science life cycle is a set of principles for doing data science work.
All problems are different, but you can still use a set of principles to help you find a solution.
You can develop and cultivate this intuition through projects.
Be sure to follow me @DataScienceHarp for more content and threads like this and share with your network if you found this helpful.
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