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A Great way to learn Data Science by simply doing it

There are tons of great online resources out there we can pick up and learn them to become a master in data science. Here is a comprehensive list of data science course providers along with links to the data science courses.

By Sumendar Karupakala.

“For the things we have to learn before we can do them, we learn by doing them” ~ ARISTOTLE


Due to the comprehensive nature of data science, which is blended with mathematics, statistics, economics, and computer science along with domain experience, hacking mindset and business implication skills, we could not find a single place where we can learn altogether, but there are tons of great online resources out there we can pick up separately and study them to become a master in data science field. If we want to expertise on this sector grab those courses from various online resources.

The challenge here is how can we choose and work on those tutorials in a smart way, Enrolling those sessions and watching videos is not only the method of doing but also we should keep on practice them on different exercise related techniques provided by those contributors on such platforms. Most of the interactive platforms offering their contents online for practice, like quiz sections, problem sets, and free datasets available for download.

Not only concentrate on technical aspects, in addition we have to put our continuous focus on various methodologies of big data analytics related to different industries perspective, because most of the companies are looking for business-savvy professionals who are well versed with industry related knowledge, more over now a day’s big data has been advancing and revolutionizing each and every sector.

I arranged below some of the best online platforms with related courses, where you can learn and practice on those topics to become a data science wizard, some of the unique features of all these courses are free to enrol and most of the providers offering accomplishment certificates by associating with their partners.


  • The Analytics Edge
  • Statistics for the Life Sciences Using R
  • Querying with Transact-SQL
  • Linear Algebra – Foundations to Frontiers
  • Knowledge Management and Big Data in Business
  • Introduction to Computer Science and Programming Using Python
  • Explore Statistics with R
  • Matrix Algebra and Linear Models
  • Statistics for Business
  • I Heart Stats: Learning to Love Statistic
  • Introduction to Computational Thinking and Data Science




  • Inferential Statistics
  • Intro to Hadoop and MapReduce
  • Data Analysis with R
  • Intro to Descriptive Statistics
  • Intro to Data Science
  • Data Visualization and D3.js





  • Introduction to Data Analysis using R
  • Hadoop Fundamentals
  • SQL Access for Hadoop



  • Try SQL
  • Try R
  • The Sequel To SQL



  • Intro to SQL: Querying and managing databases
  • Linear algebra, Probability and statistics


Stanford online lagunita: 

  • StatLearning Statistical Learning
  • CS101 Computer Science 101



  • Big Data: Measuring and Predicting Human Behaviour
  • Data to Insight: An Introduction to Data Analysis
  • Learn to Code for Data Analysis


Educast.Emc : 

  • Data Lakes for Big Data



  • Learn Python Programming From Scratch
  • R Programming Language
  • Big Data and Hadoop Essentials
  • Scraping and Data Mining
  • T-SQL for Data Analysts
  • Data Analytics using Hadoop eco system






Bio: Sumendar Karupakala is a Certified Big Data Analyst with experience in many analytical domains. He loves the tools, algorithms and techniques to enable smarter decisions using analytics with big data and data science.


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