How to Become a Data Scientist in 2019?
By: Abhishek Patnaik
Tags: Machine Learning, Python, Machine Learning Python, Data Science, Machine Learning Ai

Data Science is supposed to be the most trending field in 2019. With exposure to a large amount of data in the market and cloud services(that give GPU support), data science has become the most accessible tech for most developers.

This is one of the most common questions that I answer these days. So just thought of sharing my experience of becoming a data scientist.

So let's get started with our journey of learning data science.

One of the common mistakes which most of the new beginners do is this one:-

Directly jumping into Machine Learning/ Data Science without having any prior knowledge of Data Structures, Mathematics.

It might look cool at initial stages but what happens actually is you get stuck after some time. You might encounter a maths equation to which you are not familiar or even worse you don't know data handling properly.

Mathematics is something which is not to be scared about. No one is good at mathematics(nor was i) but you should have a clear knowledge in order to know the working’s underneath. Machine Learning is all about maths.

Take, for example, you are creating a classifier and you are using a VGG16(a classifier)network. You somehow trained the network and made it running to train on your system. Results were poor on prediction. Now you need to work on hyper-parameter tuning. What now? Yes, we can try the hit and trial process of changing the parameters but that seldom works. Until the time you know the working of a convolution like what convolution is (its maths underneath), how do optimizers work? back-propagation

why in the world do I need to do backpropagation? Wait, is there math involved in this?

be like this spider man, he knows backpropagation

It will always be a black box thing for most of us. Until we know the basics.

Read this to understand the basics of back-propagation.

We discussed a lot about flows now let's discuss how to get started on it.

First Step

Have a concrete knowledge about Data structure, basic knowledge of linear algebra.

Second Step

Have a good hand over any data science tool. In python, some of the common libraries are pandas, dask, numpy, matplotlib, seaborn etc. I prefer using the dask when the size of dataset is pretty big. Data handling is also a crucial role which a data scientist plays. Data cleaning, Data preprocessing, upscaling, downscaling, understanding the behaviour of the data is one of the most crucial parts of Data Science. I follow a simple technique:- “just like everything on this universe even data has a fixed pattern”. One needs to find the pattern in data and boom, your 50% of the task is done.

Third Step

It is the third step in which you should start off with actual machine learning. There's another common mistake which we do i.e directly starting off with neural networks. Always remember, deep learning is a way to solve machine learning problems. Before starting off with neural networks one must know the difference between a classifier, regressor, clustering.

Fourth Step

Make sure that you give urself a good amount of time understanding the basics of machine learning and have a good hand over it by building projects. Nowadays, cloud services like AWS and GCP have made GPU easily accessible to everyone.

Transfer learning is considered to be the most efficient way of starting with machine learning.

We live in an open-sourced community due to which there is no shortage of resources on the internet. When I started my career I used to spend most of my time trying out complex architecture in neural networks.

I would heavily suggest kaggle.com for the same starting off with Data Science. Another would be to get an internship so that one has good experience of how things work.

I have also seen some ads that promise to make you a Data Scientist, believe me, there is no such course that can make you a Data Scientist in 2 months. It's just a fancy ad to attract your attention. Experience is the only key that will help you become a data scientist. So don't fall prey of it.

Hackerrannk is another great platform that I would suggest as it helps in understanding data structure very well.

In case you are an engineering student and looking for videos, do refer to letsprep.in as it has AI selected videos, it brings the best videos from youtube especially for you. It has all the engineering subjects videos.

I used to follow https://www.deeplearning.ai/ at its best.

Follow me on Github as I had made a proper pipeline that would help you to get started.

Do follow me on Linkedin for more awesome content:-

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