18 Resources to Learn Data Science Online

18 Resources to Learn Data Science Online
...

R Bhargav

Last updated July 27, 2017


  • 17675 Views

It’s been called the ‘sexiest job of the 21st century’, the ‘hottest job of the decade’, and is the fastest-growing field in tech at the moment – the impact of Data Science in today’s world cannot be overstated.

But what is Data Science?

As a discipline, data science involves the collection and study of data – both structured and unstructured – to gain insights and information that can be used by organizations to devise effective strategies. By collating data over a period of time, patterns can be identified that enable companies to find new market opportunities, enhance efficiency, reduce costs, and place themselves at a competitive advantage in their industry. 

Why Data Science?

Due to rapid technological advances, especially in areas like mobile advertising, social media, and website personalization, a massive amount of data is being generated on a daily basis. These data volumes have resulted in industries having to become data-savvy & adapt to the new landscape – or risk falling behind the competition. Institutions both public and private have realized the need for Data Science implementation within their organizations. Universities have responded to this need by introducing data science courses for learners of all backgrounds.  

Why Should I Become a Data Scientist?

A recent study by McKinsey indicates that the demand for Data Scientists is on the rise, with an estimated 50% demand-supply gap by 2018.

Skilled, certified data scientists are among the highest-paid professionals in the IT industry, with the median salary for entry-level data scientists at $91,000, and managers making as much as $250,000 a year.

How Do I Become a Data Scientist?

With this in mind, we have put together a comprehensive list of Data Science courses, online tutorials, and resources to help you become a certified data scientist and build a career in the field. Whether you’re looking for full-fledged university courses or just to stay abreast of the latest developments in the industry, we’ve got something for everyone. Read on to find out more!

Preparing for a career in Data Science? Take this test to know where you stand!

Online Courses

These sites offer Data Science courses online for beginners as well as professionals.

Harvard University Data Science Certificate– This is a course that covers a number of facets under Data Science including Data Sampling, Data Management, Data Analysis, prediction, and the communication of results. To achieve a graduate credit, students must complete four of the certificate courses.

Simplilearn Data Scientist Certification Training (R, SAS & Excel)– With online training, a rigorous curriculum, and a professional certification to validate learning, this program sets learners on the fast-track to becoming a professional data scientist.

Data Science Certification Training - R Programming

Google Making Sense of Data Course- Designed to help those who work with observation data, test scores, data evaluation, demographic information, and surveys, this course helps learners identify the information that companies would want and how to decipher it. This course is ideal for everyone from small business owners to students.

California Institute of Technology Learning From Data Course– Delivered as a series of lecture videos by professor Yaser Abu-Mostafa from Caltech. Covers a range of topics, including algorithms, basic theory, and applications. Features Q&As, homework sets and a discussion forum.

Master of Information and Data Science (MIDS) at UC Berkeley School of Information - This Data Science course is targeted at professionals who are looking to use complex data to solve problems with an emphasis on asking the right questions and presenting findings in the most appropriate way. This web-based program offers live classes as well as online coursework.

Data Science Tutorials

These engaging tutorials help learners grasp the essential concepts of Data Science.

Codementor– Codementor offers tutorials for beginners and professionals. Learners can access a number of useful guides on how best to analyze data. This includes introductions to machine learning and tips on choosing the right data analytics software packages.

Topcoder - This website offers tutorials that discuss the various concepts involved in Data Science and has a platform for industry experts to offer advice. They also provide practical, real-world advice on a multitude of topics as well as start-up guides for those who are new to the site.

Analytics Vidhya- Here, learners will find a comprehensive tutorial for learning Data Science with R, including an in-depth guide that covers everything from the basics of programming and data exploration to predictive modelling and data manipulation. Other data science tutorials are available, including one on learning Data Science with Python.

KDnuggets – They offer a variety of tutorials covering everything from the processes of Data Science to how to get started with Data Visualization. The website also offers two tutorials on potential interview questions for Data Scientists that provides helpful answers and advice from the editors at KDnuggets.

R-bloggers- This tutorial covers the use of R techniques with SQL servers. There are a total of 5 lessons that walk users through the processes involved while incorporating R models into a live SQL server. There are a variety of other tutorials available on this site that offer information on the latest changes and updates in the industry.

Flowingdata - Produced by Dr. Nathan Yau, Ph.D., these tutorials offer expert advice on how to present, analyze, and understand data with practical guides to illustrate with real-time examples. Flowingdata also offers readers book recommendations, insights into the life of a Data Scientist and examples of how data can help people understand the world around them.

Additional Data Science Resources

For those looking at Data Science as a career or for those looking to enhance their learning, these sites provide in-depth information and resources on the subject:

The Open Source Data Science Masters - This website provides a variety of useful resources that will help you understand the concept of Data Science. They include books, tutorials, and study groups for a plethora of subjects from data design to computing and math. All of the information has been put together by Clare Corthell, founding partner of Data Science Consultancy, Luminant Data. 

Learnds.com- Here, learners can find a collection of materials to help when learning Data Science via IPython Notebooks. These books cover a number of key topics including random forests and linear regression, data explorations, and analyses of each area. Worksheets are also provided.

Data Science Weekly- A database of Data Science resources and news updates, this website offers readers the chance to opt into weekly newsletters which feature jobs, articles, and news. The site also offers a list of the most valuable books, data sets, and blogs alongside interviews with influential Data Scientists. 

FiveThirtyEight  - This interactive website offers Data Analysis of economic, cultural, health, sports, and political issues. The website was launched by Nate Silver. Readers can also enjoy these insightful snippets of information through podcasts.

Simply Statistics– With a huge collection of articles on the use (and misuse) of data while solving problems, this website showcases the thoughts of three biostatistics professors - Rafa Irizarry, Roger Peng and Jeff Leek. They post on everything from what inspired them to their advice to aspiring Data Scientists.

International Conference on Machine Learning - This international conference has been held in numerous locations around the world and is supported by the not-for-profit organization, the International Machine Learning Society (IMLS). Aimed at supporting machine learning, the conferences touch upon a variety of topics with participation from guest speakers and availability of workshops as well as tutorials. 

Reddit - Providing an online community that boasts of over 30,000 members, this site offers people a place to share Data Mining resources and research papers. It’s also great for Data Scientists looking to connect with like-minded people who can assist them with unique solutions to challenges.

Data is taking over the world quicker than you know. Arm yourself with the right resources. The data industry is where you need to be today. 

What are you waiting for? 

Get certified in Data Science and get ahead today! 

Watch this video on Introduction To Data Science with SAS Certification Training

Find our Big Data and Hadoop Developer Certification Training at your nearby cities:

Bangalore  Hyderabad  Chennai  Delhi  Mumbai  Pune  Toronto  Kolkata  Indore  Singapore
Sydney  Ahmedabad  Melbourne  Dallas  Coimbatore

About the Author

An experienced process analyst at Simplilearn, the author specializes in adapting current quality management best practices to the needs of fast-paced digital businesses. An MS in MechEng with over eight years of professional experience in various domains, Bhargav was previously associated with Paradox Interactive, The Creative Assembly, and Mott MacDonald LLC.


{{detail.h1_tag}}

{{detail.display_name}}
... ...

{{author.author_name}}

{{detail.full_name}}

Published on {{detail.created_at| date}} {{detail.duration}}

  • {{detail.date}}
  • Views {{detail.downloads}}
  • {{detail.time}} {{detail.time_zone_code}}

Registrants:{{detail.downloads}}

Downloaded:{{detail.downloads}}

About the On-Demand Webinar

About the Webinar

Hosted By

...

{{author.author_name}}

{{author.author_name}}

{{author.about_author}}

About the E-book

View On-Demand Webinar

Register Now!

First Name*
Last Name*
Email*
Company*
Phone Number*

View On-Demand Webinar

Register Now!

Webinar Expired

Download the Ebook

Email
{{ queryPhoneCode }}
Phone Number {{ detail.getCourseAgree?'*':'(optional)'}}

Show full article video

About the Author

{{detail.author_biography}}

About the Author

{{author.about_author}}