How can I become a Data Scientist?

Many people have asked me this question, therefore, I am creating an article out of my answer and publishing it here to help as many people as possible, so please like and share the article to make it reach where it is needed the most.

Also, I will make sure to include the tricks in my answer that worked for me.

So Let's begin, Shall we?

I will be answering this question, keeping in mind that a bunch of readers could be complete newbies into programming.

So addressing non-computer science students. Firstly, you need to work a lot on your problem-solving skills which are going to help you code effortlessly. You can achieve this by learning Data structures & Algorithms and coding in it. Also, DS & Algo are the building block of computer science so it will definitely help you on your journey towards excellence in coding.

After you are comfortable with problem-solving, you should stick to the below-mentioned points:

  1. Opt for a good course on Machine learning and study it thoroughly to become well versed with all its concepts.

  2. Practice machine learning problems on Kaggle: Your Machine Learning and Data Science Community which will help you gain confidence and give you enough hands-on skills.

  3. Post your projects on GitHub, LinkedIn and also you can use youtube to showcase your skills

  4. Now it’s time to market yourself. Make a clean and creative online portfolio and a strong resume based on ML. Start applying to your desired companies and surely circumstances will bend in your favour and soon you will become something you have worked so hard for and that is “Data scientist”

  5. You can connect with me here on LinkedIn

Ps: I am attaching my photo, in which you can see me working from home, just in case you are interested to know how a data scientist looks?! 😛


Also if you want to know how to create an online portfolio, you can check out mine to get some inspiration --> portfolio


Check out my Youtube Video on "How to Become a Data Scientist (pipeline)?" --> Video



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