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Strike the right balance between your job and AI skills with online courses.

Jason Main
June 20, 2018

As enterprises begin to take baby steps toward solving business problems with artificial intelligence, they often have difficulty finding those with the necessary skills to accompany them on their journeys. Training of prospective workers in skill sets, related to artificial intelligence has not kept pace, as demand rises for data scientists, machine learning engineers, and other related occupations. By 2020, the number of jobs in data science and analytics in the U.S. is predicted to grow by more than 2.7 million. According to a report from IBM, Burning Glass Technologies and Business Higher Education Forum, high-profile positions take longer to fill and command higher salaries than average. The New York Times reports tech giants like Google, Uber, and Facebook are raiding academia, hiring away top AI researchers and offering hefty compensation packages to do so. Companies that do not have the resources to compete for top talent would do well to grow their own by offering training opportunities to their current workforce. Many free or low-cost training resource exist online, of course, from Andrew Ng’s excellent introductory machine learning course, to the AI-focused nano degree programs on Udacity. However, top universities offering advanced degrees online through Massive Open Online Courses (MOOCs) are ushering in a higher-tier of educational opportunity. This model allows working professionals to gain the depth of knowledge and expertise they need to work effectively along with emerging technologies while staying engaged at their day jobs, and at a fraction of the cost of traditional, on-campus programs. The Georgia Institute of Technology has become the leader in this movement through its Online Master of Science in Computer Science program. OMSCS students take the same courses from the same professors as their counterparts enrolled at the university’s campus in Atlanta. They attend class in online classrooms, viewing lectures by video and collaborating with instructors and one another through message boards, streaming services, Slack and other collaboration tools. Currently, I am finishing my first year in the OMSCS program, specializing in machine learning. I have found the courses demanding. The professors and my fellow students in my class are talented, passionate, and driven to succeed. While work for my classes is often difficult and usually, time-consuming – I joke with my wife that I have taken a second job, one for which I do not get paid – I persevere because, as a full-time software developer, husband, and father of two young children. The quality and rigor of the education I receive would be difficult to match anywhere else. Not only am I getting a quality education in the fields of knowledge that will drive the coming wave of technological advancement, but I am doing so at a price that is highly affordable. My total annual educational cost is less than $2,500. Altogether, my Georgia Tech master’s degree will cost me about $8,000. Students more ambitious (or crazy) than I who take on more classes at once pay even less. The cost to me personally is effectively nothing with tuition reimbursement from my employer.  As I gain knowledge and experience in machine learning through my studies, I will be better able to help our clients face the challenges of a rapidly changing technology landscape, representing a significant return on investment in my education. The emergence of artificial intelligence as a driver of growth for enterprises requires a workforce with the skills necessary to deliver those solutions. Companies can begin to close the talent gap in AI within their own ranks by offering training opportunities for their workers through programs like Georgia Tech’s OMSCS.  

About the author

Senior Consultant | IoT & Digital Transformation
Jason Main joined Sogeti in 2013 and has worked as a software developer for higher education and retail clients as a member of the Columbus unit. He is a passionate technologist focused on building enterprise web applications, data integration tools, web services, functional and integration testing platforms for enterprise software.


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