India being a developing country, is open to more opportunities as opposed to developed countries. The possibilities here are endless, and you can pursue anything and everything you want. Meaning anyone with domain-oriented skills is an asset to the country. So how do you train as a data scientist in India? Here’s how!

First, you need to understand what exactly you will be responsible for as a data scientist:

Handling and maintaining data is one of a data scientist’s obvious and important duties. Being able to make predictions by looking at a given dataset is the whole point of being a data scientist.
Applying machine learning, statistical modelling, and artificial intelligence techniques to data science.
Asking the right questions to begin the discovery process properly.
Obtain proper results and professionally present them to the stakeholders.

Now that you know what you will be held accountable for as a data scientist, let’s see how you can become one.

1. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐛𝐞𝐟𝐨𝐫𝐞 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧

In Data Science, I did a lot of research. By reviewing the data science course curriculum and watching some videos on YouTube to get a basic understanding, we have outlined everything that is beginner friendly. Then, after investing in the course, I browsed the topic so that I wouldn’t find anything completely unusual.

2. 𝐒𝐭𝐮𝐝𝐲 𝐯𝐢𝐚 𝐟𝐫𝐞𝐞 𝐄𝐁𝐨𝐨𝐤𝐬

I am an absolute bookworm. I love books. So I searched for some free books in PDF format for complete novices in data science. I looked up the directory and started studying all the subjects I was interested in. This can be a good strategy for those without a CS background when buying a book and looking at all the topics they want to learn or learn. Taking a course is easy if you know what you are working on. Whenever you are interested in something, hit the book!

3. 𝐔𝐬𝐞 𝐟𝐫𝐞𝐞 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬, 𝐛𝐞𝐟𝐨𝐫𝐞 𝐢𝐧𝐯𝐞𝐬𝐭𝐢𝐧𝐠 𝐦𝐨𝐧𝐞𝐲

Research, you need to know that there are many free resources available on the internet. It may not be as good as what you spend on quality content, but starting from scratch is a good idea. I’ve found free resources, including books, courses, roadmaps, and project overviews/tutorials.

4. 𝐈𝐧𝐯𝐞𝐬𝐭 𝐰𝐞𝐥𝐥 𝐢𝐧 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠

After doing all this, you are ready to pay your out-of-pocket costs. You see, you can do nothing to beat the quality course you’re paying for. There are many websites where you can take online courses, and there are also places where you can attend face-to-face events. There is also a dedicated data science academy where you can register for professional development.

Think a little more about the course. Not everyone has the time to do everything I mentioned above, especially if you are already a veteran expert in technology and other disciplines.