Large enterprises, startups and high-performance businesses across industries are increasingly turning to Artificial Intelligence and advanced analytics to make faster, more effective, data-driven decisions. The volume of unstructured and structured data stored by enterprises is growing at an accelerating rate.
The demand for skilled data scientists and candidates with AI skills is at an all-time high. Yet developing those skills typically requires significant investments of time, energy and money. Businesses are struggling to successfully deploy and manage AI projects due to lack of resources. And employees interested in preparing for these highly-coveted jobs incur significant debt, and delay other strategic Business initiatives until they completed a traditional degree after business hours.
While traditional post-secondary programs in this field still have value, many working professionals are turning to online programs for a quicker, less expensive way to get started.
In 2017, IBM predicted that by 2020, demand for these skills would grow by 28% (364,000 jobs) to over 2.7 million job listings. We’ve revised that prediction, as we see growth in this space closer to 45%. A Harvard Business Review article proclaimed there is a growing war being waged for people with skills for the “sexiest job” of the 21st century, the data scientist.
More businesses than ever before are looking to fill a suite of new roles in an AI-driven world:
There are other pressing questions, too. How can existing IT professionals build specific skills for AI platforms, while they stay at their existing jobs? How can AI neophytes build the necessary skills and understanding to enter this lucrative profession, without putting their career on hold while they retrain? Nanodegrees seem to be the perfect solution.
Here are five reasons why an increasing number of people are opting for these specialized online programs to help them transition to AI careers:
Traditional classroom training is theory-based, delivered seminar-style by a career professor, from presentation slides and textbooks. By contrast, a nanodegree program uses real data science projects and machine learning models, such as:
Working through the full-lifecycle of AI projects, from planning and design to execution and results, analysis helps fledgling data scientists and researchers to hone their skills, and gain a better understanding of the strategic role AI and analytics can play in solving business challenges.
Working with real tools on realistic projects helps provide aspiring data scientists and AI developers to obtain deeper understanding into how AI platforms like Watson process data and extract insights from it. Many well-known have contributed expertise and datasets to these nanodegree programs, making the curriculum much more engaging than it would be with “dummy” data.
2. Learn from top minds in AI and data science
Nanodegrees launched by Udacity cover many technology areas such as AI or data science and are taught by active industry thought leaders. The opportunity to be coached by an accomplished data scientist like IBM’s Adam Massachi, Airbnb’s Belinda Bennett or Slack’s Stephen Morton is rare, powerful and highly sought-after. These “experts in residence in data science” answer live questions, and provide not only technical advice but also career coaching and mentorship.
