Everything I Needed to Know to Become a Job-Ready DATA SCIENTIST
I am gonna show you how I learned data science for completely FREE with a laptop and an internet connection.
First, the value of knowledge shouldn’t depend upon where that knowledge was acquired.
I mean knowledge acquired at MIT or Harvard is of no greater value than knowledge acquired elsewhere.
For example, through YouTube or blogs, or any other online resources available.
Now, even if you don’t have any access to a university and professors, you can learn all of this stuff online.
I’ve created a list of learning resources that will take you from knowing nothing and take you to the level where you have enough expertise to start applying for jobs.
It's quite 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 maths and algorithms,
be able to use these skills to gain insight into data,
and use that insight to make predictions and draw inferences.
It’s summed up well by this Venn diagram created by Drew Conway:
Some other things data scientists are expected to know are:
how to ask the right questions,
how to do great data visualizations,
how to clean their data and importantly,
they know how to communicate their findings about the data to non-data scientists.
With all that in mind, let’s look at the Learning Path that I’ve put together:
Going through the resources, it’s split into multiple sections.
The Python Basics
Little bit more Python
Data Exploration and Visualization
Some Kaggle Tutorials
Probability and Statistics
Python and Data Science
Data Structures and Algorithms in Python
a) Intro to SQL
Git and Version-Control
a) Pro Git
Some Supplementary Materials
This book can help you: How to Think Like a Computer Scientist.
You have to become a part of different communities. It’s important for Networking and learning from others. It can be forums or discord servers.
Here is a Slack community you can join: KaggleNoobs
We are learning to get a genuine job so it’s really 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 that you’ve learned.
You should post at least once a week.
I haven’t included a lot of R resources. I don’t want to overwhelm you with lots of stuff.
And if you’ve never done any programming before it’s easier just to learn one language at a time.
But, you will need to know R programming as well.
If you are reading this and decide to skim through the resources, it’s fine but make sure to take this class:
It’s a Harvard course on Data Science and it is superb. So, make sure you do that.
All of the listed resources are 100% FREE. Some of them need you to sign in with your Google or GitHub account and that's it.
I’m still searching for other useful and interesting resources and I will be adding them to future blogs.
Keep in mind that projects are really important.
Make sure you do lots of projects and try to do a capstone(Peak-level) project every three months.
This is a marathon rather than a sprint and it’s gonna take you a little while. So, good luck and let me know how good you get.
And make sure you blog what you’re doing. You can send the blogs to me and I’d love to share some of them through my Medium.