Ok, so the title is a little provocative, but some people are dubious that data science training is even possible, because they believe data science entails skills one can learn only on the job and not in a classroom. I am not in that camp, although I do believe that data science is something you learn by doing, with an emphasis on both the learning and the doing. So how and where can you learn to do data science, if you want to become data scientist lady?

There is no agreed-upon definition of data science, but I like to think of it as three legs of a stool - strong quantitative foundation, excellent programming skills, and keen understanding of business and communication. A quantitative foundation is most often learned in university, but as I've written previously the disciplines studied can range from statistics to archaeology, and it can pay to go recruiting outside the traditional academic disciplines. A solid academic background is an invaluable start, although I hear business complain that many graduates are not prepared for real life problems, where data can be messy and/or sparse and you may not have the luxury of an elegant solution. More and more academic programs incorporate case studies, practicums, internships, etc. Earlier this year Tom Davenport hosted a Tweetchat on the top ten ways businesses can influence analytics education, which is a good read if you want to influence the graduate pipeline. There are even emerging PhD programs in Data Science.

Programming skills are a second leg of the stool. While there are many classes in universities that incorporate the use of software, more and more people seek to learn on their own, whether they be current students or working professionals. MOOCs have become increasingly popular, with many turning first to a source like Coursera to find the content they want. SAS jumped into this game with the launch last year of SAS® University Edition. This new offering was designed to address the demand we hear for those who want to learn SAS, as well as those who want to hire students with SAS skills, This offering has proven very popular — as of today it has been downloaded over 407,000 times, from Afghanistan to Zimbabwe. While it is called University Edition, it is available for anyone seeking to learn for non-commercial purposes. The SAS Analytics U Community offers a ton of free resources to help your learning, including tutorials, e-learning, a discussion board, etc. It's a powerful offering, with no limitations on data you use and accessible as a downloadable package of selected SAS products that runs on Windows, Linux and Mac.

The third leg of the stool is business acumen and the ability to communicate well. These are the skills that are hardest to pick up in a university program and may be best learned on the job. One shortcut could be the SAS Academy for Data Science, which is  an intensive data science certification program that combines hands-on learning and case studies in a collaborative environment. In addition to covering key topics like machine learning, time series forecasting, and optimization, students will learn important programming skills in a blended approach with SAS, Hadoop, and open source technologies. There's even a module on Communicating Technical Findings with a Non-Technical Audience. The Academy covers all the content necessary to sit for the new Big Data Certification and Data Science Certification that SAS is offering.

If these topics are of interest to you and you'll be attending the SAS Analytics 2015 Conference in Las Vegas October 26-27 you're in luck! On Monday Dr. Jennifer Priestley of Kennesaw State University is giving a talk on Is It Time for a PhD in Data Science? On Tuesday afternoon Cat Truxillo will be talking about our new certifications for data science in a table talk called World-Class Data Science Certification From the Experts. And my colleague Sharad Prabhu and I will be leading a table talk on Tuesday afternoon on SAS^® University Edition – Connecting SAS^® Software in New Ways to Develop More SAS^® Users. If you're there come join us!

 image credit: photo by nraden // attribution by creative commons