Data Science

5 steps to become a good data scientist !

After talking about data science, little presentation, today we’re going to talk about how to become a data scientist.

Now you’re certainly thinking that you need a masters or Phd degree from a great university in order to be a data scientist, well of course it’s true if you have a masters or a Phd from a really top university that’s gonna open doors for you, but you don’t need that to be a data scientist, today we’re going to know how do it.

There are a 5 steps to be a data scientist, I’m going to go through them quickly now, and then I’m gonna repeat them in a little bit more detail after wards, first you need to learn Python, two you need to learn math specifically linear algebra calculs and statistics, number 3 you need to learn some python libraries, number four you must to practice how do you do  that when you need to register with a site like a kaggle.com, It’s a great choice go to their site and go on the learn, and follow some of the paths there, number 5 you need to register with github so you can share what you’ve been doing with the world.

Let’s go into the detail to the number one :

  • Learn python :

Python is a great language for data science, but there will be those people who say that you don’t learn python you learn R, not are you wanna learn MATLAB, just not listen to them yet, it’s true one day you need to learn R, you will need to learn MATLAB, but at least you might to begin with python is the best choice, just take it from it. So if you need to know hwo to learn Python well I’ve got some resources on that article, you can visit this website.

  • Learn math :

Data science is all about applying math to data so if you don’t know math you’re not able to do data science, but not fear math can be learned easily and there are some great resources online you’re gonna need to learn linear algebra, calculs and statistics, start with Khan academy it’s free, and there are some great resources on calculs and linear algebra, also try the MIT courses on YouTube they are absolutely fantastic and free some great courses  in single variable calculs and multivariable calculs. Check out blue one brown it’s great on linear algebra.

  • Learn a python library:

The python libraries are absolutely fantastic if you don’t know what a library it’s basically something that you can add to python that gives python a load more functionality, you are going need to learn Numpy and Sumpy  they’re the maths ones you’re going to learn pandas that’s the data analytics one and helping you shape and yourshape your data, and have a look and see what’s inside the data it’s a fantastic library for that data visualization you can do a little bit of that with pandas, but if you want to look at data visulazition seriously you’re gonna need Matplotib and Seaborn, and then finnaly the most important for data science is scikit-learn, it’s contains algorithms that are popular in machine learning and data science and it give you easy way to implement those algorithms and you’re gonna need to master Scikit-learn.

  • Practice :

Go into Kaggle, find some great data sets on CAC or go into to their learning pathways, spend a much time as you can explore a data on kaggle and it’s every time you do a project on Kaglle.  

  • Upload yours projects :

Every time you do a project for yourself upload your code to Github try to upload one project per monthn and that’s way you building your own Profilio, and then employers you know in the future.