How to get started with data science

Data really powers everything that we do. — Jeff Weiner

Photo by Markus Spiske on Unsplash

Guys how many of you are fascinated by the fact that we are using self-Driving cars and robots which resemble humans

When we see the underlying technology in these amazing creations we will see data science play a major role in this.

Why Harvard business review gives data scientist sexiest job in the industry right now??

Link to the article:

Data Scientist: The Sexiest Job of the 21st Century

You’re probably asking yourself what exactly is data science??

So let’s see what is data science…..

Can you tell me what is the most important resource a person needs in 21st century??

The world’s most valuable resource is no longer oil, but data

What has changed? Smartphones and the internet have made data abundant, ubiquitous and far more valuable. Whether you are going for a run, watching TV or even just sitting in traffic, virtually every activity creates a digital trace more raw material for the data distilleries. As devices from watches to cars connect to the internet, the volume is increasing

This aspect of data science is all about uncovering findings from data. Diving in at a granular level to mine and understand complex behaviors, trends, and inferences. It’s about surfacing hidden insight that can help enable companies to make smarter business decisions.

Skills Required to become a data scientist

Computer science skills could be the ability to cleverly draw up code from scratch to solve problems; math and statistics would allow you to just do math and stats to data; but substantive expertise would let you use your background in biology to apply those things to finding diseases in DNA codes. If you don’t have substantive expertise, you usually don’t even know what to do with your technical skills that matters, even if you do have any technical skills.

Programming Language used for data science

Python is one of the most popular language for data science

By surfing the internet, I was able to find that python was easier to learn than R while on the other hand R had a high learning curve as compared to Python. This reminded me the quote by mark Zuckerberg:

“If you do the things that are easier first, then you can actually make a lot of progress”

Common Libraries used for data science

1. Numpy (Data analysis)
2. Pandas (Data analysis)
3. Matplotlib (Plots and charts)
4. scikit-learn(Machine Learning )
5. Bokeh (Data visualization)
6. Nltk(Natural language processing)

“Data is the oil of the 21st century, and analytics is the combustion engine”

CONCLUSION

This is my first article on medium and sharing my knowledge is the best way to learn more. I am doing various projects on data science continuously and regularly. And most importantly I am still learning and growing every day. My goal is to become a better person than what I was yesterday and this should truly be yours goal too in any situation in life.

Hope you all liked the post.Make sure to like and share it. Happy learning!!.

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1. Linkedin — https://www.linkedin.com/in/neelesh-gupta-55793b13a/
2. Github — https://github.com/Neelesh7544
3. Medium — https://medium.com/@neeleshgupta_38530
4. Twitter — https://twitter.com/shadowchastiser

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