Learning path & resources to start your data science (analytics) career today

Kunal Jain 31 Jan, 2017
3 min read

Marie said it correctly – the most difficult step in any process is the first step!Start your analytics career today

 

Recently, we launched a list of various analytics trainings being offered across the globe and are still adding more trainings to it to make it more comprehensive. While we get the entire page up and ready for you, I thought let me start putting down ways in which this information would be helpful to people.

What better place to start, than to help out the people who need it the most? Yes you are right…I am talking about people who want to start their journey in analytics or are in very initial stages of doing so. For the purpose of this article, I’ll also assume that you are motivated to take this journey in self learning mode. If you are not or need higher degree of assistance, you can easily go back to the listing page and substitute these resources for paid ones based on their ratings and subject matter.

These resources should make you knowledge ready for your first job in analytics industry

 

Choice of Language:.

I strongly believe that the choice of your first language should be a mainstream one! It helps you get a lot of resources and large community / tech support to fall back upon. For this reason, you should either choose R or SAS. You can also think of Python, WEKA or Matlab, but I would suggest R or SAS over them. Between R & SAS, you can not go much wrong – SAS has the biggest market share and R is catching up fast. Both offer free versions for learning, which you can download for learning the software. If you are still confused about the choice, you can read a detailed comparison here.

 

Books to read:

To understand power of analytics:

These books provide a good overview of how analytics can impact our business decisions and thought process, challenges faced in implementing data based solutions and also its limitations (the last one).

Freakonomics by Steven D. Levitt

Moneyball by Michael Lewis

Scoring points by Clive Humby and Terry Hunt

When Genius Failed by Roger Lowenstein

 

Gearing up on the subject:

The Signal and the Noise by Nate Silver

Big Data – A revolution that will transform How we live, work and think

Web Analytics 2.0 by Avinash Kaushik

 

Video based trainings:

Learning the basics:

Linear Algebra and Statistics from Khan Academy – All the basics you would need explained in awesome way! You realize how learning can be fun when you see them for the first time

Intro to Descriptive Statistics on Udacity & Inferential Statistics on Udacity – for the activity filled classes and exercises they provide.

 

For learning tools

Base SAS and Statistics course from SAS Institute – If you choice of tool is SAS

SAS Analytics U tutorials from SAS Institute (again if SAS is your choice)

Data Science Specialization from John Hopkins University on Coursera – If you want to take learning in relaxed manner (3 – 4 hours every week over a period on 9 months)

edX Analytics Edge (R) – For those who can sustain more intensive schedule (20 – 25 hours every week for 3 months)

Google Analytics certification by Google – if you want to build a career in Web Analytics

Chandoo.org for learning and refreshing Excel – it contains some nice tips and tricks.

Qlikview / Tableau Tutorial – I think you should learn one of these visualization tools, so that you can draw powerful visualizations quickly

 

Other Reference material:

SAS Analytics U – download center

SAS documentation & SUGI papers

CRAN project website for downloading R and packages

Videos from Google on R (available on YouTube)

R documentation

 

For staying up to date with the industry

Subscribe to following blogs;

 

Do you think I have missed out on any resources, which can be immensely valuable to a newbie in this industry? If so, please feel free to add them here.

If you like what you just read & want to continue your analytics learningsubscribe to our emailsfollow us on twitter or like our facebook page.

Kunal Jain 31 Jan, 2017

Frequently Asked Questions

Lorem ipsum dolor sit amet, consectetur adipiscing elit,