DEMYSTIFYING DATA SCIENCE: A BEGINNER’S GUIDE

If you haven’t heard the term “Data Science”, then you are lagging behind the time my friend.
“Data Scientist: The Sexiest Job of the 21st Century” - Harvard Business Review.

What is Data Science?
Let’s keep this short and simple, Data Science is a science of making sense of data.

Saying goes that data is the new oil. While big Data engineers take care of extracting the crude oil, transporting to tankers, routing through pipelines and then storing it into massive storehouse, it is the data scientists who refined the crude oil.
Data Science is the art of finding what we don’t know from data. It is about creating data products that can be useful for decision making. Data science helps in building …show more content…
Understanding of statistics will help you interpret data that you have collected and analyzed.
Data Science become magical when brilliant mathematical concepts are applied to the data yielding unexpected insights.
Basic concepts include Descriptive and Inferential statistics, linear algebra, graphing etc.

PROGRAMMING AND DATABASES:
This is the domain which will separate you from statistician and analysts. For any given data, you need to write programs to query and retrieve data from the databases or you may apply machine learning algorithms.
You should have good grasp on data science libraries and modules.
Talking about Python and R, both are good programming languages to start with as both provides some pre-built libraries that can be used just by importing them into programs.

Some common packages of both programming language:

Database Systems act as central hub to store information. These can be SQL based or NO SQL based.
Relational Database includes PostgreSQL, MySQL, Oracle etc. and others are Hadoop, Spark, and MongoDb etc.

DOMAIN …show more content…
Machine learning is used to create predictive models.
Machine Learning algorithms are really powerful, you won’t need to create one new algorithm but you should know the common ones from dimensionality reduction to supervised and unsupervised algorithms.

Algorithms like: You’ve used machine learning dozens of times in a day, Google Search :) this works so well because machine learning software knows how to rank pages. When Facebook recognizes you friends in your picture that’s also is Machine Learning.

All the tools and resources will help to solve problems but your goal should be finding right tool or model to be used and most important asking right questions.

How can we solve real world problems with Data Science?
Data Science is making an impact in areas far and wide. Data Science isn’t about thinking of tech problems. It is a tool that can be used to solve problems in a variety of fields.

NETFLIX: It uses collaborative filtering algorithms to recommend movies to the users based on movies they have previously watched.

SOCIAL MEDIA: Many social media sites are also using data science. Recommending new connections on LinkedIn or recommending products on Amazon, personalizing your Facebook feeds or suggesting new people to follow on