Everything I needed to know to become a ready-to-use DATA SCIENTIST | by Aditya Ghimire | November 2022
I’ll show you how I learned data science for completely FREE with laptop and internet connection.
First, the value of knowledge should not depend on where that knowledge was acquired.
I mean that the knowledge acquired at MIT or at Harvard is of no greater value than knowledge acquired elsewhere.
For example, through YouTube or blogs, or any other available online resource.
Now, even if you don’t have access to a university and professors, you can learn it all online.
I created a list of learning resources it will take you of knowing nothing and bring you to the level where you have enough expertise to start applying for jobs.
It’s a long list so make yourself comfortable.
So, what does a data scientist do?
Data science is a broad term that covers a number of skills.
A data scientist will know:
how to code,
have a good understanding of mathematics and algorithms,
be able to use these skills to better understand the data,
and use this information to make predictions and draw conclusions.
It’s nicely summed up by this Venn diagram created by Drew Conway:
Some other things data scientists are supposed to know are:
how to ask the right questions,
how to make great data visualizations,
how to clean your data and especially,
they know how to communicate their conclusions about the data to non-data scientists.
With all that in mind, let’s look at the Learning path which I collected:
This book can help you: How to think like a computer scientist.
You have to be part of different communities. It is important for Networking and learn from others. These can be forums or discord servers.
Here’s a Slack community you can join: KaggleNoobs
We learn to find a real job it is therefore very important that you write a blog and that put all your projects on GitHub.
I can’t stress how important it is to write a blog about your experience with data science. Also, teach the concepts you have learned.
You should post at least once a week.
I didn’t include a lot of R Resources. I do not want overwhelm you with lots of things.
And if you have never done any programming before it’s easier just to learn one language at a time.
But, you’ll need to know R Programming as well.
a) Tutorials for R
If you’re reading this and decide to browse the resources, that’s fine, but make sure take this course:
Data Science by Harvard.
It’s a Harvard course in data science and it’s superb. So make sure you do.
All resources listed are 100% FREE. Some of them need you to sign in with your Google or GitHub account and that’s it.
I am always looking for other useful and interesting resources and I will be add them to future blogs.
Keep in mind that projects are really important.
Make sure you do a lot of projects and try to do a capstone project (max level) every three months.
It’s a marathon rather than a sprint and it will take you a little while. So good luck and let me know how good you get.
And make sure you blog what you do. You can send me the blogs and I would like to share some of them through my medium.