Day 1: Where to begin!

Data Analytics and Science, I hear these terms  so often these days. Institutes are offering post graduate degrees for learning data science, and there are numerous paid e-learning wesites on data science. I am a Computer Science graduate, and in my undergraduate curriculum we had very little scope of Data Science. I have some knowledge on Machine Learning, Prolog and Python. Everyone says that data science is the future, every decision will be based on data but I don't want to spend a ton of money learning it. So every day, I will spend around 1 hour, to learn something new on Data Science from cheap sources and see if I can really learn it. 

The most confusing part for me is what is what! We have Data Science, and there is Data Analytics and Data Vizualization. So today I will be clearing the terms.

• Data Science:  It is the science of extracting information from huge amount of data using various tools and technology. Everything else can be clubbed under it, like Data Analytics, Data  Vizualization, Machine Learning, etc. 

• Machine Learning: Programming a Machine to think and act like a Human (includes extracting data, categorizing data, using statistics to predict).

• Data Analysis: It is to extract information from raw data using statistical tools, ML and based on that data take decisions.  

• Data Mining: It is the process of  finding a pattern from raw data using statistics, ML etc

• Data Vizualization: It is a graphical representation of data, which is useful in finding patterns and other informations

• Big Data: Huge volume of unstructured or structured data.