What are the steps to become a data scientist in India or abroad?

Updated on : December 6, 2021 by Ashton Gallagher



What are the steps to become a data scientist in India or abroad?

Hey! The best way to get started in data science would be to acquire the necessary skills and techniques. This can be achieved by making use of online courses and tutorials, as they are mostly offered for free. They often provide a certification that is valued in the industry. Once the relevant skills have been acquired, one can practice with new and advanced databases and start connecting with recruiters to get a good position.

There is this website called 'EdAuthority' that provides information and reviews on career and learning opportunities in data science. I hope this helps :)

The right way is self-study by doing things yourself. Remember that it is a challenging path and at some point you feel like you have to give up once it gets harder and everything seems so difficult.

But there is a way. I am giving the links. It is not too mathematical, but rather what is mainly needed in industry.

Note: I followed a different little path, but everyone has to choose what suits them best.

First check out my article on what machine learning is and if you can understand what I have explained. This will clear things up before setting your goal. If you don't understand what I explained there, I doubt that

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The right way is self-study by doing things yourself. Remember that it is a challenging path and at some point you feel like you have to give up once it gets harder and everything seems so difficult.

But there is a way. I am giving the links. It is not too mathematical, but rather what is mainly needed in industry.

Note: I followed a different little path, but everyone has to choose what suits them best.

First check out my article on what machine learning is and if you can understand what I have explained. This will clear things up before setting your goal. If you don't understand what I explained to you there, I doubt you can go all the way.

Here's that link: Rahul Akhouri's answer to What are the prerequisites to start learning machine learning?

Now I will give you some links:

Statistics:

Sometimes we ignore it, but it is imperative for your fundamentals to be correct and to broaden your perspective towards data analysis.

Introduction to Udacity Statistics

Probability and statistics by CMU

Statistical modeling

Statisticians say statistical modeling and machine learning for computer engineers. But they are both about the same, except when you study statistical modeling, you focus more on statistical terms like hypothesis testing and uncertainty. While machine learning focuses exclusively on the problem to be solved.

ISLRs written by Stanford professors are the best to start with. You also have a YOUTUBE VERSION of the book. For more advanced learning and using mathematical treatment, study ESLR (for this you must be an expert in calculus)

For the guys at PHD, you must have already known about these books. ISLR is good for those who are not experts in statistics.

I highly recommend that you check everything out.

Machine learning:

Computer Science people solve a problem using 'Algorithms' and Statistics people using 'Techniques'. You will find the same content in both machine learning and statistical modeling, but the approach is different.

Geogia TECH

Google

Google Deep Learning

This is all. You would need programming languages ​​like R or Python. Choose only one. If you are an engineer choose Python, otherwise choose R.

R programming

Introduction to Python programming

Introduction to data analysis in Python

So as you can see, you can't master each and every one. But learn up to machine learning and then choose 'Data Analyst' or 'NLP' or 'AI'. It is in increasing order of complexity.

Analyst / Data Visualization:

It requires you to explore patterns in the data by reviewing the data manually. Plot charts, etc. This is also in high demand. These will also allow you to do great jobs, if not as good as machine learning / statistical modeling.

SQL

Picture

Georgia Tech Data Visualization

Natural language processing:

Requires good programming skills (Python), data cleansing (regex), and NLP techniques with knowledge of machine learning / deep learning (required). There is a lot of demand for the NLP engineer.

Image processing:

You must master deep learning to perform effective image processing such as object detection / facial recognition etc.

Google Deep Learning

AI Engineer:

Artificial intelligence is sometimes confused with machine learning / programming. The thing is, great statisticians are not inclined to solve computer problems. Therefore, we need a computer scientist who can write smart algorithms and apply machine learning.

AI by Georgia Tech

Introduction to AI

AI for robotics

I hope that helps.

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