WEEK_1: Introduction to Data Science

Hi there!

I am Sharath G S. I have started to learn Data Science.

This booming field was introduced to me by the organization I am working with.

I want to be a master of Data Science. So I have done a lot of research about Data Science. I will be sharing my learnings here. I will post on weekly basis. I will try to summarize my learnings of the week in a single post.

First of all, we need to understand what is Data Science. The very first thing that we do is just 'Google it'. Even I did the same.

Here is how wikipedia defines Data Science.

"Data Science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analysis, similar to Knowledge Discovery in Databases (KDD)."

Data Science often involves using mathematic and algorithmic techniques to solve some of the most analytically complex business problems, leveraging troves of raw information to figure out hidden insight that lies beneath the surface. It centers around evidence-based analytical rigor and building robust decision capabilities.

Data Science enables companies to operate and strategize more intelligently. That is the reason why Data Science is the booming field.

Here is an image which will summarize the role of Data Science.

Who is Data Scientist?

"A data scientist is simply someone who is highly adept at studying large amounts of often unorganized/undigested data."

Another definition for a Data Scientist.

"A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician."

I found a Data Scientist's learning map. You don't have to worry about this now. This is just for your reference!

Data Science learner's path

You need to be good with statistics to become a good Data Scientist. You can refer the Probability and statistics course by Khanacademy. Follow this link to access the course.

We will start with Data Analysis. 


This is how this page define data analysis.

"Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data."


We can use R language or Python for this purpose. I would like to go with R.
Let us start with R language next week. We will be doing text mining and analysis in the next session. And you know what? It is real fun! You will be doing sentiment analysis of your Twitter tweets and WhatsApp chats.

Don't miss it, subscribe to the blog for all updates.

Thanks for visiting my blog. I always love to hear constructive feedbacks. Please give your feedback in the comment section below or write to me personally here.
(I use R-Bloggers for updates on R, consider visiting this blog too!)