Agree or not Data Science is booming nowadays with more and more companies adopting it as a tool for driving key insights from their data. Even Harvard Business Review have named “Data Scientist” as sexiest job of 21th century. Some of states in USA are becoming HUB for data science related activity.
Below is complete guide for Data Science Resources: –
Stats play a quite crucial role in the Data Science Lifecyle and helps in understanding data and draw conclusions from it using different concepts like Probability Theory, Central Limit Theorem etc. In order to learn Statistics watch the following tutorial lecture. Although it’s quite long lecture but it covers all of required stuff for data science. This tutorial is presented by Dr. Abhinanda Sarkar Ph. D. from Stanford University in Statistics.
Most of Data Scientist typically use Python/R/SQL programming language in their day-to-day job role. Python and R is used for doing Data Analysis or Data Visualisation while SQL is used for dealing with data(like retrieving data from a database or writing to database).
There are many resources for learning Python available online, but below is list of resources which I’ve personally used for learning Python.
Moreover watch following tutorial which is presented by experts from freecodecamp ->
R programming language is as important as Python in Data Science. There are some features which R have but Python and vice-versa. Thus both of these programming languages are complementary to each other. On the top of that having R as a skill would enhance profile for job role as Data Scientist.
Following is the list of resources which I’ve used in order to learn R programming language.
Watch following tutorial as well quite helpful for understanding how R can be used practically ->
SQL is a domain-specific language used in programming and designed for managing data held in a relational database management system, or for stream processing in a relational data stream management system.
In Data Science domain it’s used vastly specifically for storing data collected. For example – In case of a Retailer data about sales made can be stores in a database. Now if Data Scientist want to retrieve that data then SQL is required.
Below are resources for learning SQL ->
In order to learn how to apply SQL practically watch following tutorials ->