What it takes to build artificial intelligence skills

What it takes to build artificial intelligence skills

Artificial intelligence, AI, is all the rage these days -- analysts are proclaiming it will change the world as we know it, vendors are AI-washing their offerings, and business and IT leaders are taking a close look at what it can potentially deliver in terms of growth and efficiency.

For people at the front lines of the revolution, that means developing and honing skills in this new dark art. In this case, AI requires a blend of programming and data analytics skills, with the necessary business overlay.

In a recent report at the Dice site, William Terdoslavich explores some of the skills people will need to develop a repertoire in the AI space, noting that these skills are in high demand, especially with firms such as Google, IBM, Apple, Facebook, and Infosys absorbing all available talent.

Machine learning is the foundational skill for AI, and online courses such as those offered through Coursera offer some of the fundamental skills. Abdul Razack, senior VP and head of platforms at Infosys, notes that another way to develop AI expertise is to "take a statistical programmer and training them in data strategy, or teach more statistics to someone skilled in data processing."

Mathematical knowledge is also foundational, Terdoslavich adds, requiring a "solid grasp of probability, statistics, linear algebra, mathematical optimization--is crucial for those who wish to develop their own algorithms or modify existing ones to fit specific purposes and constraints."

Programs popular with AI developers include R, Python, Lisp, Prolog and Scala, Terdoslavich's article states. Older standbys -- such as C and C++ and Java -- are also being employed, depend upon applications and performance requirements. Platforms and toolsets such as TensorFlow also provide AI capabilities.

Ultimately, becoming adept in AI also requires a degree of a change in conceptual thinking as well, requiring deductive reasoning and decision-making.

AI skills -- again, which blend expertise n programming, data, and business development -- may continue to be in short supply, and David Kosbie, Andrew W. Moore, and Mark Stehlik sounded the alarm in a recent Harvard Business Review article, calling for an overhaul of computer science programs at all levels of education. AI is "not something a solitary genius cooks up in a garage," they state. "People who create this type of technology must be able to build teams, work in teams, and integrate solutions created by other teams."

This requires a change in the way programming is taught, they add.

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