In some cities, the demand for tech pros skilled in artificial intelligence (A.I.) has intensified to the point where some companies are hosting internal classes in the technology. Facebook, for example, offers A.I. classes to employees that typically fill to capacity within minutes. Those formal sessions, combined with research internships, are designed to fill the company with tech pros who are capable of building A.I. into every product they touch. Nor is Facebook alone; according to Wired, Google is also rushing to educate its employees in everything A.I.-related. The thinking goes something like this: with outside (i.e., hirable) talent so limited, it’s better to take the already-smart people within the company walls and train them in concepts such as machine learning and deep neural networks. The benefits are obvious: while employees won’t become artificial intelligence experts overnight (or even within a few months), they can rapidly apply the concepts they learn to whatever they’re working on, translating into immediate strategic gains. The alternative might involve waiting until an expert is available and willing to be poached—and that could take quite some time. And if tech companies (especially startups) lack anything, it’s time. Even if your company hasn’t instituted an "artificial intelligence school” in-house, there are certainly ways to bone up on the latest in artificial intelligence and machine learning. Google has been so kind as to offer a three-hour course, via its Google Cloud Platform Website, in deep learning, a methodology for building effective machine-learning tools. That course teaches “a few basic network architectures, including dense, convolutional and recurrent networks, and training techniques such as dropout or batch normalization.” It instructs in a few ways to solve “typical problems with neural networks,” as well as some vocabulary and concepts related to A.I. Facebook also offers instructional materials, most notably a series of videos that break down fundamental A.I. concepts, including algorithms (useful for anyone who wants a job actually using A.I.). The videos also cover the different categories of A.I. learning, including reinforcement learning, supervised learning, and unsupervised or predictive learning. Last but certainly not least, online courses such as Udacity offer instruction in A.I.; you can also teach yourself some of the same aspects of via materials on GitHub. Whatever method you choose, it’s become increasingly clear that a little bit of A.I. knowledge can go a long way when applying for jobs that have anything to do with software. Knowing A.I. Concepts Can Boost Your Value
In some cities, the demand for tech pros skilled in artificial intelligence (A.I.) has intensified to the point where some companies are hosting internal classes in the technology. Facebook, for example, offers A.I. classes to employees that typically fill to capacity within minutes. Those formal sessions, combined with research internships, are designed to fill the company with tech pros who are capable of building A.I. into every product they touch. Nor is Facebook alone; according to Wired, Google is also rushing to educate its employees in everything A.I.-related. The thinking goes something like this: with outside (i.e., hirable) talent so limited, it’s better to take the already-smart people within the company walls and train them in concepts such as machine learning and deep neural networks. The benefits are obvious: while employees won’t become artificial intelligence experts overnight (or even within a few months), they can rapidly apply the concepts they learn to whatever they’re working on, translating into immediate strategic gains. The alternative might involve waiting until an expert is available and willing to be poached—and that could take quite some time. And if tech companies (especially startups) lack anything, it’s time. Even if your company hasn’t instituted an "artificial intelligence school” in-house, there are certainly ways to bone up on the latest in artificial intelligence and machine learning. Google has been so kind as to offer a three-hour course, via its Google Cloud Platform Website, in deep learning, a methodology for building effective machine-learning tools. That course teaches “a few basic network architectures, including dense, convolutional and recurrent networks, and training techniques such as dropout or batch normalization.” It instructs in a few ways to solve “typical problems with neural networks,” as well as some vocabulary and concepts related to A.I. Facebook also offers instructional materials, most notably a series of videos that break down fundamental A.I. concepts, including algorithms (useful for anyone who wants a job actually using A.I.). The videos also cover the different categories of A.I. learning, including reinforcement learning, supervised learning, and unsupervised or predictive learning. Last but certainly not least, online courses such as Udacity offer instruction in A.I.; you can also teach yourself some of the same aspects of via materials on GitHub. Whatever method you choose, it’s become increasingly clear that a little bit of A.I. knowledge can go a long way when applying for jobs that have anything to do with software. 
