DATA SCIENCE

INTRODUCTION

Playing with data is called data science. And if we are playing with data digitally then our happiness gets doubled because that involves a lot of mind involvement and coding, algorithms, language different type of mathematical skills, etc. But remember the journey is not so easy but as nowadays every data are saved in databases not in papers so the demand of this skill is increasing day by day.

DATA SCIENCE OPPORTUNITY?

As India is now putting its steps towards digitalization you will find a lot of opportunity in data science. And be sure you will be in high demand with a minimum salary of 10lacks per anum. Some important facts 

• According to research by times of India, 62% expected increase in demand for data science this year due to digitalization.
• Stepping stone was the jio revolution which increased the no of internet users in India indirectly increasing the use of data scientists.
• All big companies national like Paytm to Flipkart to google are in demand of data scientist always

HOW TO BECOME A DATA SCIENTIST 

Data scientist mandatory skillsets

1.Mathematics and Statistics

Data science is such a field in technology direction which requires math more than learning a language. Not all maths are required but some specific maths like

• statistics for analyzing results for others
• differentiation of function for drawing graphs
• Gradient, maxima, and minima of a function
• Require a heavy knowledge in MS excel Probability
• Permutations and combinations basic levels.

In advance states, you require to learn Mathematics useful for Machine Learning programs.

2. Programming

You can try data science and machine learning algorithms under any language but preferable is python due to its advanced libraries and ease to learn. So, most popular MNCs use python for their works so it is now a compulsion for us to learn data science in python. 

Learn about Python Basics and C++ (basic friendly), Then Numpy, Pandas, Matplotlib, or Seaborn. Time complexity is the most important one for the reprogramming field. You also need to learn database languages like SQL, MySQL, NoSQL, etc.

3. Big Data and External Data Visualization Tools (Optional)

Python can be used for doing everything in machine learning and data science at a beginner and intermediate stage but after some time you may require Tableau, Excel, Hadoop, AWS Offerings. In advance state, you have to learn this surely and these are very time killing also.

4. Machine learning (M/L)and Deep Learning

Machine learning is a part of data science in which we automate the analysis by computers, in machine learning, we create a program by taking some already existing data sets and then create an artificial brain by feeding that data sets to the machines, and later that machines program create stereotype programs to check in your absence and improve himself by taking other data.

5. Linux and git and GitHub for version control

As in data science, we deal with a lack of dozens of data it is impossible to do by one man so to collaborate with other peoples we need git and git-hub like version controls.