Here’s an analytical solution provided on how to become a billionaire.

You might be excited by reading the title. “Billionaire” — such a fancy word, right?

Who am I to write about this topic? Am I one of the billionaires? — Obviously, NO!!. But I wish I were one.

Am I writing this to give any financial tips or advice to become a billionaire? — NOPE.

Then, whom am I? And what are we going to do here? — I am an analyst with the Forbes billionaire historical dataset. We are going to play with the data and answer the 10 most critical questions.

Are you excited to know what are…

We all know that the probability of getting heads in a coin flip is 50%. Is it really true?

Let’s imagine a situation that you are making a bet with your friend. The game goes like this — you have to flip a coin 50 times. If tails land up more, then you have to pay $10 to your friend and vice-versa. And also the coin is a perfectly normal coin. No tricks involved in that. Now, the question is that, “Can you test your odds and go with the game?”

You would have studied probability in your high school…

Learn how to make your stories more engaging

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Creating charts and graphs is easy. Extracting the story from those graphs is challenging. So a Data Analyst role is not to make attractive visuals; a graphic designer could do that. The vital part of a data analyst is to make sure that the audience can evoke precise information via those graphs. Not everyone can read data. It’s our duty as data analysts to explain those graphs and charts with an exciting story.

  1. Make the audience curious — This is the first and foremost step to follow. Presenting data is like showcasing a movie to the audience. The introduction decides…

Here’s the complete road-map to learn Data Science from “Zero to Hero” with source links provided.

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Table of contents — Learning path:

  1. Introduction
  2. Soft skills required for Data Science
  3. Python — basics
  4. Python libraries — Numpy, Pandas and Matplotlib
  5. SQL
  6. Tableau/Power BI
  7. Data analysis using Python
  8. Statistics and Probability
  9. Machine learning Algorithms
  10. Deep learning (Neural Networks)
  11. Project ideas
  12. Building profile and portfolio development
  13. Conclusion

If you hate programming? But still, want to pursue in Data analysis field? Check out this blog on Data Analysis for non-programmers.

1. Introduction:

As you have clicked on this blog to read this, you might have some knowledge or interest in Data Science. Since it is an emerging field, most of you might be curious to learn about it…

Bored with learning new technologies in Data Science & IT? Need hands-on experience with real-world projects? Add weightage to your Resume?

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Need to practice your Data analytics skills? And get certified within hours?

Yeah!! You are on the right path. Here I will show you how to apply for virtual internships for Data Science and furthermore developing technologies.

  1. Go to → You will see a window like this.

Planning on the transition towards Data Analysis? But do you hate programming? Here’s the complete road-map for you.

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If you are not a person who is attracted towards coding but to pursue in the data-driven field. Then “Data Analyst” is the right job designation for you.

Now you might ask “What it takes to become a Data analyst?” Here are the super handy skills you must need to master:

  1. MS Excel
  2. Tableau/Power BI
  3. SQL
  4. Interest to explore something new😉

1. MS Excel:

You might seem surprised by seeing the word “MS Excel”. You might think that “MS Excel is a tool mastered by even 8th-grade students. You are telling me to learn MS Excel😂”. If your current mind voice is this…

Hari Prasad

MS in Data Science at Columbia University | Curious explorer looking forward to solving business problems as a Data Scientist.

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