Actionable steps for experienced professionals to get into Data Science

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You have years of experience and want to move into data science.

Here are actionable steps to follow for all experienced professionals

First things first, Data Science is a field that can be integrated into any domain, since all domains have data.

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You do not need to start from zero even if you have years of experience.

How?

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1/ You are not at the 0th level

Understand this if you have n years of experience in any field you do not need to start from 0 in data science, as this field can be applied in any area of the domain.?

If you drop your previous field, the experience becomes zero and now you are a fresher. Obviously, you don't want that.?

Use your current knowledge and see how it can be integrated with data science.

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2/ Strong Fundamentals

Develop a strong understanding of the fundamentals of data science. This includes learning about topics such as statistics, programming, data analysis, and machine learning.?

You can do this through online courses, boot camps, or a formal education program.

Start with Python and Logic Building here:

https://github.com/hemansnation/Python-Roadmap-2022

3/ Roadmap of Full Stack Data Science

Everything you need to know for data science.

?https://github.com/hemansnation/Data-Science-ML-Full-Stack-2022

4/ Huge and Complex Data

Gain experience working with real-world data. This can include participating in online data science competitions, working on personal projects, or interning or volunteering with organizations that use data science.

Kaggle Datasets: https://www.kaggle.com/datasets

You can read my thread on Twitter for 1000+ dataset resources:

Note: Only work on problems that are already in your domain of expertise.

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5/ Strong GitHub profile

GitHub is social media for developers and programmers. You can build one using these steps:

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6/ Portfolio of Projects

Build a portfolio of your data science projects and accomplishments. This can include projects you've worked on, papers you've published, or presentations you've given on data science topics.

Write blogs on how you built the project and what challenges you have overcome. This will give a sense of achievement and the recruiter proof of work.

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7/ Network with Data Scientists

Network with other data scientists and professionals in the field. This can include attending conferences and events, joining online communities and forums, or connecting with data scientists on LinkedIn.

Don't be afraid to ask for help or clarification when you need it, and keep learning and growing as a Data Scientist.

Connect with me on LinkedIn here:

Join the MasterDexter Data Science Community

Telegram: https://t.me/+sREuRiFssMo4YWJl

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8/ No Certifications

If you answer the questions in an Interview the certificate doesn't count if you don't answer, well again certificate will not count.

Built projects

Deploy them

Get use cases.

Focus on solving actual business problems any much as you can, that is what Data Science is all about.

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That's a wrap!

Are you interested in these topics:

?Python, Machine Learning, Data Science, Data Engineering, Computer Vision, NLP, Business Problems?

Follow Himanshu Ramchandani and get amazing content in the field.